Last updated on 2024-09-26 00:50:19 CEST.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 0.5.5 | 238.02 | 333.04 | 571.06 | OK | |
| r-devel-linux-x86_64-debian-gcc | 0.5.5 | 185.28 | 261.88 | 447.16 | OK | |
| r-devel-linux-x86_64-fedora-clang | 0.5.5 | 1076.80 | NOTE | |||
| r-devel-linux-x86_64-fedora-gcc | 0.5.5 | 1098.61 | ERROR | |||
| r-devel-windows-x86_64 | 0.5.5 | 277.00 | 432.00 | 709.00 | NOTE | |
| r-patched-linux-x86_64 | 0.5.5 | 274.87 | 344.34 | 619.21 | OK | |
| r-release-linux-x86_64 | 0.5.5 | 260.22 | 343.82 | 604.04 | OK | |
| r-release-macos-arm64 | 0.5.5 | 257.00 | NOTE | |||
| r-release-macos-x86_64 | 0.5.5 | 425.00 | NOTE | |||
| r-release-windows-x86_64 | 0.5.5 | 253.00 | 429.00 | 682.00 | NOTE | |
| r-oldrel-macos-arm64 | 0.5.5 | 262.00 | NOTE | |||
| r-oldrel-macos-x86_64 | 0.5.5 | 405.00 | NOTE | |||
| r-oldrel-windows-x86_64 | 0.5.5 | 319.00 | 521.00 | 840.00 | NOTE |
Version: 0.5.5
Check: installed package size
Result: NOTE
installed size is 6.2Mb
sub-directories of 1Mb or more:
doc 2.2Mb
libs 2.2Mb
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-windows-x86_64, r-release-macos-arm64, r-release-macos-x86_64, r-release-windows-x86_64, r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64
Version: 0.5.5
Check: examples
Result: ERROR
Running examples in ‘hesim-Ex.R’ failed
The error most likely occurred in:
> ### Name: CohortDtstmTrans
> ### Title: Transitions for a cohort discrete time state transition model
> ### Aliases: CohortDtstmTrans
>
> ### ** Examples
>
> library("msm")
> library("data.table")
> set.seed(101)
>
> # We consider two examples that have the same treatment strategies and patients.
> # One model is parameterized by fitting a multi-state model with the "msm"
> # package; in the second model, the parameters are entered "manually" with
> # a "params_mlogit_list" object.
>
> # MODEL SETUP
> strategies <- data.table(
+ strategy_id = c(1, 2, 3),
+ strategy_name = c("SOC", "New 1", "New 2")
+ )
> patients <- data.table(patient_id = 1:2)
> hesim_dat <- hesim_data(
+ strategies = strategies,
+ patients = patients
+ )
>
> # EXAMPLE #1: msm
> ## Fit multi-state model with panel data via msm
> qinit <- rbind(
+ c(0, 0.28163, 0.01239),
+ c(0, 0, 0.10204),
+ c(0, 0, 0)
+ )
> fit <- msm(state_id ~ time, subject = patient_id,
+ data = onc3p[patient_id %in% sample(patient_id, 100)],
+ covariates = list("1-2" =~ strategy_name),
+ qmatrix = qinit)
*** caught segfault ***
address 0x1, cause 'memory not mapped'
Traceback:
1: Ccall.msm(params, do.what = "lik", ...)
2: fn(par, ...)
3: (function (par) fn(par, ...))(c(qbase = -1.26716112628169, qbase = -4.39086558334109, qbase = -2.28239038570853, qcov = 0, qcov = 0))
4: optim(method = "BFGS", control = list(), par = c(qbase = -1.26716112628169, qbase = -4.39086558334109, qbase = -2.28239038570853, qcov = 0, qcov = 0), fn = function (params, ...) { assign("nliks", get("nliks", msm.globals) + 1, envir = msm.globals) args <- list(...) w <- args$msmdata$subject.weights if (!is.null(w)) { lik <- Ccall.msm(params, do.what = "lik.subj", ...) sum(w * lik) } else Ccall.msm(params, do.what = "lik", ...)}, hessian = TRUE, gr = function (params, ...) { w <- list(...)$msmdata$subject.weights if (!is.null(w)) { deriv <- Ccall.msm(params, do.what = "deriv.subj", ...) apply(w * deriv, 2, sum) } else Ccall.msm(params, do.what = "deriv", ...)}, msmdata = list(mf = list(strategy_name = c(3L, 3L, 3L, 1L, 1L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 3L, 3L, 3L, 1L, 1L, 3L, 3L, 3L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 2L, 2L, 2L, 3L, 3L, 3L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 3L, 3L, 2L, 2L, 2L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 3L, 3L, 1L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 1L, 1L, 1L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 2L, 2L, 2L), `(subject)` = c(1L, 1L, 1L, 127L, 127L, 209L, 209L, 250L, 250L, 267L, 267L, 267L, 280L, 280L, 285L, 285L, 285L, 378L, 378L, 378L, 440L, 440L, 440L, 478L, 478L, 488L, 488L, 500L, 500L, 507L, 507L, 507L, 528L, 528L, 528L, 569L, 569L, 569L, 612L, 612L, 612L, 677L, 677L, 678L, 678L, 678L, 787L, 787L, 787L, 827L, 827L, 829L, 829L, 829L, 860L, 860L, 860L, 890L, 890L, 905L, 905L, 905L, 950L, 950L, 966L, 966L, 1005L, 1005L, 1005L, 1010L, 1010L, 1010L, 1013L, 1013L, 1013L, 1016L, 1016L, 1016L, 1045L, 1045L, 1045L, 1151L, 1151L, 1151L, 1201L, 1201L, 1201L, 1204L, 1204L, 1204L, 1244L, 1244L, 1244L, 1263L, 1263L, 1263L, 1269L, 1269L, 1269L, 1270L, 1270L, 1270L, 1308L, 1308L, 1308L, 1315L, 1315L, 1315L, 1393L, 1393L, 1439L, 1439L, 1441L, 1441L, 1441L, 1447L, 1447L, 1486L, 1486L, 1486L, 1520L, 1520L, 1545L, 1545L, 1545L, 1572L, 1572L, 1572L, 1575L, 1575L, 1580L, 1580L, 1580L, 1619L, 1619L, 1633L, 1633L, 1633L, 1687L, 1687L, 1687L, 1695L, 1695L, 1695L, 1728L, 1728L, 1728L, 1742L, 1742L, 1752L, 1752L, 1761L, 1761L, 1761L, 1807L, 1807L, 1807L, 1847L, 1847L, 1847L, 1861L, 1861L, 1866L, 1866L, 1866L, 1869L, 1869L, 1877L, 1877L, 1906L, 1906L, 1911L, 1911L, 1911L, 1981L, 1981L, 1981L, 2025L, 2025L, 2028L, 2028L, 2073L, 2073L, 2073L, 2097L, 2097L, 2141L, 2141L, 2141L, 2143L, 2143L, 2143L, 2173L, 2173L, 2173L, 2187L, 2187L, 2187L, 2199L, 2199L, 2218L, 2218L, 2218L, 2223L, 2223L, 2223L, 2263L, 2263L, 2263L, 2312L, 2312L, 2314L, 2314L, 2314L, 2366L, 2366L, 2366L, 2371L, 2371L, 2371L, 2435L, 2435L, 2435L, 2446L, 2446L, 2446L, 2448L, 2448L, 2598L, 2598L, 2598L, 2619L, 2619L, 2801L, 2801L, 2816L, 2816L, 2816L, 2817L, 2817L, 2817L, 2823L, 2823L, 2836L, 2836L, 2864L, 2864L, 2864L, 2865L, 2865L, 2865L, 2870L, 2870L, 2879L, 2879L, 2879L), `(state)` = c(1, 2, 3, 1, 1, 1, 1, 1, 1, 1, 2, 3, 1, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 3, 1, 3, 1, 1, 1, 2, 3, 1, 2, 2, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 3, 1, 3, 1, 1, 1, 2, 3, 1, 2, 2, 1, 2, 3, 1, 2, 3, 1, 2, 2, 1, 2, 3, 1, 2, 2, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 2, 1, 2, 3, 1, 2, 2, 1, 2, 2, 1, 3, 1, 3, 1, 2, 2, 1, 1, 1, 2, 3, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 3, 1, 3, 1, 2, 2, 1, 2, 3, 1, 2, 2, 1, 2, 2, 1, 3, 1, 1, 1, 2, 3, 1, 2, 2, 1, 2, 2, 1, 3, 1, 2, 2, 1, 3, 1, 3, 1, 3, 1, 2, 2, 1, 2, 2, 1, 1, 1, 1, 1, 2, 3, 1, 3, 1, 2, 2, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 1, 1, 2, 2, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 2, 1, 2, 3, 1, 2, 2, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 2, 3, 1, 2, 3, 1, 3, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 3), `(time)` = c(0, 2.42022603865082, 14.6202584741099, 0, 1.06335115169736, 0, 3.37846853071824, 0, 5.91722974553704, 0, 4.58288009058403, 9.52924055461131, 0, 6.05977787502578, 0, 5.11314795230023, 14.1889426135388, 0, 3.9793853225728, 9.98404531133461, 0, 1.82958139332304, 11.7164812447244, 0, 8.25267813210891, 0, 5.28795059607339, 0, 2.40431244601521, 0, 3.27374095025703, 5.53660267247331, 0, 1.83614749739054, 6.8820353038609, 0, 2.32244494219243, 7.30246650986373, 0, 7.99197312290447, 15, 0, 0.373379818629473, 0, 9.97610073141581, 12.6211857463451, 0, 3.75908505063792, 6.51468300260603, 0, 5.07091985782608, 0, 1.69717255488757, 7.01308546587825, 0, 7.06069513880918, 15, 0, 1.8811577023007, 0, 4.90076951101563, 9.2030299551945, 0, 8.91516227995197, 0, 0.777970170602202, 0, 3.76012797928306, 12.7541593079442, 0, 5.4803828995153, 13.1962402455088, 0, 4.57313999656492, 13.0845508557175, 0, 5.63132673670023, 13.3382248074442, 0, 9.6100249037167, 10.6032960983524, 0, 1.60594620632657, 12.4776779445559, 0, 3.88422755035061, 5.87685098173097, 0, 5.19510834409654, 8.05593266150475, 0, 2.15403129570777, 11.8152541148148, 0, 3.43228499180158, 12.4636539884778, 0, 5.44870446876656, 12.0652837486224, 0, 6.88192152582238, 13.4552436723617, 0, 8.02066811347412, 15, 0, 4.50021161766982, 6.28881715788393, 0, 4.95045249025033, 0, 1.94473282188878, 0, 1.23358175813834, 3.81546577904373, 0, 2.45351897996223, 0, 5.75103343570654, 12.8507074011371, 0, 3.13150474335998, 0, 3.62361482018708, 15, 0, 1.70753057440278, 2.90423630503938, 0, 4.71622260985896, 0, 4.68820884543174, 10.6059529059576, 0, 5.67809275410179, 0, 5.74954350923768, 11.1949939368018, 0, 2.16842943591225, 9.5564392590454, 0, 4.11827209679337, 5.9958520391956, 0, 6.26891657464451, 11.293289180075, 0, 3.89833941377084, 0, 2.06416486447456, 0, 4.41538331020301, 10.4442594197434, 0, 5.51281272877163, 9.3304296140559, 0, 14.5558520209811, 15, 0, 3.96473119041544, 0, 6.82327246979789, 15, 0, 6.62903601714705, 0, 7.15516451563556, 0, 3.99949697666245, 0, 5.92132857335279, 8.07890239404514, 0, 5.72167968614231, 9.83430769527331, 0, 1.7716667172499, 0, 5.90151765849441, 0, 4.48052619859954, 12.8467609089349, 0, 3.71839352901634, 0, 4.42204647988183, 13.1059182373277, 0, 0.645748993758942, 5.43988305911687, 0, 2.22858722279899, 11.2371628721608, 0, 6.74261799564098, 10.4231144904582, 0, 0.588790811598301, 0, 6.71063269816809, 15, 0, 1.69891210470069, 7.27827564580366, 0, 6.63979810625763, 9.28839638130739, 0, 0.3010408510454, 0, 11.7159918790512, 15, 0, 7.42690194298182, 13.4159356094477, 0, 7.50595106923712, 15, 0, 10.496191308296, 10.8230564317884, 0, 0.503689229919938, 3.92409760504961, 0, 1.68466971058728, 0, 10.394417598933, 15, 0, 0.167301606852561, 0, 5.043442575261, 0, 4.30473713445075, 13.5908252629751, 0, 5.52245333077557, 13.1322277836806, 0, 6.52321177528359, 0, 4.89751752465963, 0, 4.06238924789648, 12.5009299948098, 0, 6.76183990406097, 15, 0, 0.463039907882884, 0, 3.19690445223537, 13.2164889044032), `(obstype)` = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), `(obstrue)` = c(1, 2, 3, 1, 1, 1, 1, 1, 1, 1, 2, 3, 1, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 3, 1, 3, 1, 1, 1, 2, 3, 1, 2, 2, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 3, 1, 3, 1, 1, 1, 2, 3, 1, 2, 2, 1, 2, 3, 1, 2, 3, 1, 2, 2, 1, 2, 3, 1, 2, 2, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 2, 1, 2, 3, 1, 2, 2, 1, 2, 2, 1, 3, 1, 3, 1, 2, 2, 1, 1, 1, 2, 3, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 3, 1, 3, 1, 2, 2, 1, 2, 3, 1, 2, 2, 1, 2, 2, 1, 3, 1, 1, 1, 2, 3, 1, 2, 2, 1, 2, 2, 1, 3, 1, 2, 2, 1, 3, 1, 3, 1, 3, 1, 2, 2, 1, 2, 2, 1, 1, 1, 1, 1, 2, 3, 1, 3, 1, 2, 2, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 1, 1, 2, 2, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 2, 1, 2, 3, 1, 2, 2, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 2, 3, 1, 2, 3, 1, 3, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 3), `(obs)` = 1:256, `(pcomb)` = c(NA, 1L, 2L, NA, 3L, NA, 4L, NA, 5L, NA, 6L, 7L, NA, 8L, NA, 9L, 10L, NA, 11L, 12L, NA, 13L, 14L, NA, 15L, NA, 16L, NA, 17L, NA, 18L, 19L, NA, 20L, 21L, NA, 22L, 23L, NA, 24L, 25L, NA, 26L, NA, 27L, 28L, NA, 29L, 30L, NA, 31L, NA, 32L, 33L, NA, 34L, 35L, NA, 36L, NA, 37L, 38L, NA, 39L, NA, 40L, NA, 41L, 42L, NA, 43L, 44L, NA, 45L, 46L, NA, 47L, 48L, NA, 49L, 50L, NA, 51L, 52L, NA, 53L, 54L, NA, 55L, 56L, NA, 57L, 58L, NA, 59L, 60L, NA, 61L, 62L, NA, 63L, 64L, NA, 65L, 66L, NA, 67L, 68L, NA, 69L, NA, 70L, NA, 71L, 72L, NA, 73L, NA, 74L, 75L, NA, 76L, NA, 77L, 78L, NA, 79L, 80L, NA, 81L, NA, 82L, 83L, NA, 84L, NA, 85L, 86L, NA, 87L, 88L, NA, 89L, 90L, NA, 91L, 92L, NA, 93L, NA, 94L, NA, 95L, 96L, NA, 97L, 98L, NA, 99L, 100L, NA, 101L, NA, 102L, 103L, NA, 104L, NA, 105L, NA, 106L, NA, 107L, 108L, NA, 109L, 110L, NA, 111L, NA, 112L, NA, 113L, 114L, NA, 115L, NA, 116L, 117L, NA, 118L, 119L, NA, 120L, 121L, NA, 122L, 123L, NA, 124L, NA, 125L, 126L, NA, 127L, 128L, NA, 129L, 130L, NA, 131L, NA, 132L, 133L, NA, 134L, 135L, NA, 136L, 137L, NA, 138L, 139L, NA, 140L, 141L, NA, 142L, NA, 143L, 144L, NA, 145L, NA, 146L, NA, 147L, 148L, NA, 149L, 150L, NA, 151L, NA, 152L, NA, 153L, 154L, NA, 155L, 156L, NA, 157L, NA, 158L, 159L)), mf.agg = list(strategy_name = c(2L, 3L, 1L, 1L, 3L, 3L, 1L, 2L, 1L, 2L, 3L, 1L, 3L, 2L, 3L, 3L, 2L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 1L, 3L, 1L, 2L, 3L, 1L, 3L, 2L, 2L, 3L, 3L, 1L, 1L, 1L, 3L, 1L, 2L, 1L, 2L, 3L, 3L, 2L, 3L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 1L, 2L, 2L, 2L, 3L, 1L, 3L, 2L, 1L, 1L, 3L, 2L, 3L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 3L, 3L, 1L, 3L, 2L, 3L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 1L, 2L, 2L, 3L, 2L, 2L, 2L, 2L, 3L, 1L, 1L, 2L, 3L, 1L, 3L, 1L, 2L, 1L, 2L, 2L, 1L, 3L, 2L, 2L, 3L, 2L, 3L, 1L, 2L, 2L, 1L, 2L, 3L, 3L, 3L, 1L, 1L, 1L, 3L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 3L, 3L, 2L, 1L, 2L, 2L, 1L, 1L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 2L, 3L, 1L, 3L, 3L), `(subject)` = c(2619L, 2312L, 2435L, 677L, 1847L, 2870L, 2446L, 2199L, 2143L, 966L, 1045L, 127L, 1572L, 1441L, 1151L, 2448L, 829L, 2223L, 1572L, 2025L, 1315L, 440L, 528L, 1695L, 890L, 1439L, 1201L, 2879L, 2598L, 2435L, 1151L, 1545L, 2314L, 1L, 1847L, 1752L, 1244L, 1911L, 1687L, 2173L, 507L, 569L, 500L, 1L, 1447L, 1441L, 678L, 2263L, 787L, 1204L, 1520L, 2879L, 507L, 2314L, 209L, 2446L, 1263L, 1545L, 2187L, 2097L, 787L, 1005L, 1807L, 1201L, 1742L, 1861L, 378L, 1906L, 2864L, 1981L, 1695L, 905L, 2816L, 1761L, 2141L, 2073L, 1315L, 1013L, 267L, 2598L, 1580L, 1575L, 2143L, 2836L, 905L, 267L, 1393L, 569L, 1728L, 2801L, 528L, 827L, 285L, 1204L, 488L, 829L, 1633L, 1269L, 1010L, 1807L, 2817L, 2223L, 1016L, 1619L, 1981L, 1633L, 1486L, 2028L, 250L, 1580L, 1911L, 2366L, 378L, 1761L, 280L, 1728L, 2823L, 1270L, 1269L, 1869L, 2263L, 2218L, 2187L, 2865L, 1866L, 1270L, 1308L, 612L, 860L, 1486L, 1877L, 1687L, 2366L, 2371L, 2371L, 2817L, 1016L, 1010L, 860L, 612L, 1308L, 1866L, 2865L, 478L, 2218L, 2073L, 2864L, 1013L, 2141L, 950L, 1005L, 2173L, 1263L, 285L, 2816L, 1045L, 1244L, 440L, 678L), `(fromstate)` = c(1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 2, 2, 1, 1, 2, 2, 1, 2, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 2, 2, 2, 2, 2, 1, 1, 1, 2, 1, 2, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 2, 1, 2, 2, 1, 2, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 2, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2, 1, 2, 1, 2, 1, 2, 2, 2, 2, 1, 1, 2, 2, 1, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 1, 2, 2, 1), `(time)` = c(0, 0, 10.496191308296, 0, 14.5558520209811, 0, 0, 0, 0, 0, 9.6100249037167, 0, 1.70753057440278, 0, 0, 0, 0, 0, 0, 0, 4.50021161766982, 0, 0, 4.11827209679337, 0, 0, 3.88422755035061, 3.19690445223537, 0, 0, 1.60594620632657, 3.62361482018708, 0, 2.42022603865082, 0, 0, 0, 5.92132857335279, 0, 0, 3.27374095025703, 0, 0, 0, 0, 1.23358175813834, 9.97610073141581, 6.63979810625763, 3.75908505063792, 5.19510834409654, 0, 0, 0, 11.7159918790512, 0, 0.503689229919938, 0, 0, 6.74261799564098, 0, 0, 0, 5.51281272877163, 0, 0, 0, 0, 0, 0, 5.72167968614231, 0, 4.90076951101563, 0, 0, 0, 0, 0, 0, 0, 10.394417598933, 0, 0, 0.645748993758942, 0, 0, 4.58288009058403, 0, 2.32244494219243, 6.26891657464451, 0, 1.83614749739054, 0, 0, 0, 0, 1.69717255488757, 5.74954350923768, 0, 0, 0, 0, 1.69891210470069, 0, 0, 0, 0, 0, 0, 0, 4.68820884543174, 0, 7.42690194298182, 3.9793853225728, 4.41538331020301, 0, 0, 0, 6.88192152582238, 5.44870446876656, 0, 0, 0, 0, 0, 0, 0, 8.02066811347412, 7.99197312290447, 0, 5.75103343570654, 0, 2.16842943591225, 0, 7.50595106923712, 0, 5.52245333077557, 5.63132673670023, 5.4803828995153, 7.06069513880918, 0, 0, 6.82327246979789, 6.76183990406097, 0, 6.71063269816809, 4.48052619859954, 4.06238924789648, 4.57313999656492, 4.42204647988183, 0, 3.76012797928306, 2.22858722279899, 3.43228499180158, 5.11314795230023, 4.30473713445075, 0, 2.15403129570777, 1.82958139332304, 0), `(obstype)` = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), `(obstrue)` = c(1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 2, 2, 1, 1, 2, 2, 1, 2, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 2, 2, 2, 2, 2, 1, 1, 1, 2, 1, 2, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 2, 1, 2, 2, 1, 2, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 2, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2, 1, 2, 1, 2, 1, 2, 2, 2, 2, 1, 1, 2, 2, 1, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 1, 2, 2, 1), `(obs)` = c(233L, 211L, 223L, 43L, 160L, 253L, 225L, 200L, 191L, 66L, 81L, 5L, 128L, 114L, 83L, 228L, 53L, 205L, 127L, 179L, 108L, 22L, 34L, 144L, 59L, 112L, 87L, 256L, 230L, 222L, 84L, 125L, 213L, 3L, 159L, 151L, 92L, 174L, 140L, 194L, 32L, 37L, 29L, 2L, 117L, 115L, 46L, 209L, 49L, 90L, 122L, 255L, 31L, 214L, 7L, 226L, 95L, 124L, 198L, 186L, 48L, 68L, 157L, 86L, 149L, 162L, 19L, 171L, 247L, 177L, 143L, 62L, 237L, 153L, 188L, 183L, 107L, 74L, 11L, 231L, 132L, 130L, 192L, 245L, 61L, 12L, 110L, 38L, 147L, 235L, 35L, 51L, 16L, 89L, 27L, 54L, 138L, 98L, 71L, 156L, 240L, 206L, 77L, 135L, 176L, 137L, 119L, 181L, 9L, 133L, 173L, 217L, 20L, 154L, 14L, 146L, 243L, 102L, 99L, 167L, 208L, 202L, 197L, 250L, 164L, 101L, 105L, 41L, 56L, 120L, 169L, 141L, 216L, 220L, 219L, 241L, 78L, 72L, 57L, 40L, 104L, 165L, 251L, 25L, 203L, 184L, 248L, 75L, 189L, 64L, 69L, 195L, 96L, 17L, 238L, 80L, 93L, 23L, 45L), `(tostate)` = c(1, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 2, 2, 1, 2, 2, 2, 1, 2, 2, 2, 2, 1, 3, 2, 3, 2, 2, 3, 2, 2, 3, 2, 1, 2, 2, 2, 2, 3, 2, 1, 2, 1, 2, 2, 2, 2, 3, 1, 2, 2, 2, 1, 2, 2, 2, 3, 3, 2, 2, 2, 2, 3, 3, 2, 3, 2, 2, 2, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 3, 1, 2, 3, 3, 2, 2, 1, 2, 1, 2, 2, 3, 2, 2, 2, 2, 2, 2, 2, 2, 3, 2, 2, 2, 1, 1, 3, 2, 3, 3, 3, 3, 2, 3, 3, 2, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 2, 2, 2, 3, 3, 2, 2, 2, 2, 2, 2, 3, 2, 3, 2, 3, 2, 3, 3, 3, 3, 3, 3, 2, 3, 3, 2), `(timelag)` = c(0.167301606852561, 0.3010408510454, 0.326865123492345, 0.373379818629473, 0.444147979018943, 0.463039907882884, 0.503689229919938, 0.588790811598301, 0.645748993758942, 0.777970170602202, 0.993271194635708, 1.06335115169736, 1.19670573063659, 1.23358175813834, 1.60594620632657, 1.68466971058728, 1.69717255488757, 1.69891210470069, 1.70753057440278, 1.7716667172499, 1.78860554021411, 1.82958139332304, 1.83614749739054, 1.87757994240222, 1.8811577023007, 1.94473282188878, 1.99262343138036, 10.0195844521678, 10.394417598933, 10.496191308296, 10.8717317382293, 11.3763851798129, 11.7159918790512, 12.2000324354591, 14.5558520209811, 2.06416486447456, 2.15403129570777, 2.15757382069236, 2.16842943591225, 2.22858722279899, 2.26286172221628, 2.32244494219243, 2.40431244601521, 2.42022603865082, 2.45351897996223, 2.58188402090539, 2.64508501492929, 2.64859827504976, 2.75559795196811, 2.86082431740821, 3.13150474335998, 3.19690445223537, 3.27374095025703, 3.28400812094883, 3.37846853071824, 3.42040837512967, 3.43228499180158, 3.62361482018708, 3.68049649481719, 3.71839352901634, 3.75908505063792, 3.76012797928306, 3.81761688528427, 3.88422755035061, 3.89833941377084, 3.96473119041544, 3.9793853225728, 3.99949697666245, 4.06238924789648, 4.112628009131, 4.11827209679337, 4.30226044417887, 4.30473713445075, 4.41538331020301, 4.42204647988183, 4.48052619859954, 4.50021161766982, 4.57313999656492, 4.58288009058403, 4.60558240106704, 4.68820884543174, 4.71622260985896, 4.79413406535793, 4.89751752465963, 4.90076951101563, 4.94636046402728, 4.95045249025033, 4.9800215676713, 5.02437260543045, 5.043442575261, 5.04588780647037, 5.07091985782608, 5.11314795230023, 5.19510834409654, 5.28795059607339, 5.31591291099067, 5.44545042756416, 5.44870446876656, 5.4803828995153, 5.51281272877163, 5.52245333077557, 5.57936354110297, 5.63132673670023, 5.67809275410179, 5.72167968614231, 5.74954350923768, 5.75103343570654, 5.90151765849441, 5.91722974553704, 5.91774406052587, 5.92132857335279, 5.98903366646586, 6.00465998876181, 6.02887610954037, 6.05977787502578, 6.26891657464451, 6.52321177528359, 6.57332214653931, 6.61657927985586, 6.62903601714705, 6.63979810625763, 6.71063269816809, 6.74261799564098, 6.76183990406097, 6.82327246979789, 6.88192152582238, 6.97933188652588, 7.00802687709553, 7.06069513880918, 7.09967396543056, 7.15516451563556, 7.38800982313315, 7.42690194298182, 7.49404893076288, 7.50595106923712, 7.60977445290499, 7.706898070744, 7.71585734599353, 7.93930486119082, 7.99197312290447, 8.02066811347412, 8.17672753020211, 8.23816009593903, 8.25267813210891, 8.28936730183191, 8.36623471033537, 8.43854074691333, 8.51141085915261, 8.68387175744583, 8.91516227995197, 8.99403132866118, 9.00857564936184, 9.03136899667618, 9.07579466123855, 9.2860881285244, 9.6100249037167, 9.66122281910707, 9.88689985140138, 9.97610073141581), `(nocc)` = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), `(whicha)` = 1:159, `(noccsum)` = c(NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 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mm.icov = NULL, subject.weights = NULL), qmodel = list(nstates = 3L, iso = 4, perm = c(1, 2, 3), qperm = 1:3, npars = 3, imatrix = c(0, 0, 0, 1, 0, 0, 1, 1, 0), qmatrix = c(-0.29402, 0, 0, 0.28163, -0.10204, 0, 0.01239, 0.10204, 0), inits = c(0.28163, 0.01239, 0.10204), constr = 1:3, ndpars = 3L, expm = 1), qcmodel = list( npars = 6, ndpars = 6, ncovs = 2, constr = c(1, 2, 3, 4, 5, 6), covlabels = c("strategy_nameNew 1", "strategy_nameNew 2" ), inits = c(0, 0, 0, 0, 0, 0), covmeans = c(`strategy_nameNew 1` = 0.352201257861635, `strategy_nameNew 2` = 0.314465408805031), cri = c(1, 0, 0, 1, 0, 0)), cmodel = list(ncens = 0, censor = NULL, states = NULL, states_list = NULL, index = NULL), hmodel = list(hidden = FALSE, models = c(0, 0, 0), nipars = 0, nicoveffs = 0, totpars = 0, ncoveffs = 0, ematrix = FALSE), paramdata = list(inits = c(qbase = -1.26716112628169, qbase = -4.39086558334109, qbase = -2.28239038570853, qcov = 0, qcov = 0), plabs = c("qbase", "qbase", "qbase", "qcov", "qcov", "qcov", "qcov", "qcov", "qcov"), allinits = c(qbase = -1.26716112628169, qbase = -4.39086558334109, qbase = -2.28239038570853, qcov = 0, qcov = 0, qcov = 0, qcov = 0, qcov = 0, qcov = 0), hmmpars = integer(0), fixed = FALSE, fixedpars = c(qcov = 5L, qcov = 6L, qcov = 8L, qcov = 9L), optpars = c(1L, 2L, 3L, 4L, 7L), auxpars = integer(0), constr = c(1, 2, 3, 4, 5, 6, 7, 8, 9), npars = 9, duppars = integer(0), nfix = 4L, nopt = 5L, ndup = 0L, ranges = c(0, 0, 0, -Inf, -Inf, -Inf, -Inf, -Inf, -Inf, Inf, Inf, Inf, Inf, Inf, Inf, Inf, Inf, Inf), params = c(qbase = -1.26716112628169, qbase = -4.39086558334109, qbase = -2.28239038570853, qcov = 0, qcov = 0, qcov = 0, qcov = 0, qcov = 0, qcov = 0)))
5: do.call("optim", optim.args)
6: msm.optim.optim(p = list(inits = c(qbase = -1.26716112628169, qbase = -4.39086558334109, qbase = -2.28239038570853, qcov = 0, qcov = 0), plabs = c("qbase", "qbase", "qbase", "qcov", "qcov", "qcov", "qcov", "qcov", "qcov"), allinits = c(qbase = -1.26716112628169, qbase = -4.39086558334109, qbase = -2.28239038570853, qcov = 0, qcov = 0, qcov = 0, qcov = 0, qcov = 0, qcov = 0), hmmpars = integer(0), fixed = FALSE, fixedpars = c(qcov = 5L, qcov = 6L, qcov = 8L, qcov = 9L), optpars = c(1L, 2L, 3L, 4L, 7L), auxpars = integer(0), constr = c(1, 2, 3, 4, 5, 6, 7, 8, 9), npars = 9, duppars = integer(0), nfix = 4L, nopt = 5L, ndup = 0L, ranges = c(0, 0, 0, -Inf, -Inf, -Inf, -Inf, -Inf, -Inf, Inf, Inf, Inf, Inf, Inf, Inf, Inf, Inf, Inf), params = c(qbase = -1.26716112628169, qbase = -4.39086558334109, qbase = -2.28239038570853, qcov = 0, qcov = 0, qcov = 0, qcov = 0, qcov = 0, qcov = 0)), gr = function (params, ...) { w <- list(...)$msmdata$subject.weights if (!is.null(w)) { deriv <- Ccall.msm(params, do.what = "deriv.subj", ...) apply(w * deriv, 2, sum) } else Ccall.msm(params, do.what = "deriv", ...)}, hessian = TRUE, msmdata = list(mf = list(strategy_name = c(3L, 3L, 3L, 1L, 1L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 3L, 3L, 3L, 1L, 1L, 3L, 3L, 3L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 2L, 2L, 2L, 3L, 3L, 3L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 3L, 3L, 2L, 2L, 2L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 3L, 3L, 1L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 1L, 1L, 1L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 2L, 2L, 2L), `(subject)` = c(1L, 1L, 1L, 127L, 127L, 209L, 209L, 250L, 250L, 267L, 267L, 267L, 280L, 280L, 285L, 285L, 285L, 378L, 378L, 378L, 440L, 440L, 440L, 478L, 478L, 488L, 488L, 500L, 500L, 507L, 507L, 507L, 528L, 528L, 528L, 569L, 569L, 569L, 612L, 612L, 612L, 677L, 677L, 678L, 678L, 678L, 787L, 787L, 787L, 827L, 827L, 829L, 829L, 829L, 860L, 860L, 860L, 890L, 890L, 905L, 905L, 905L, 950L, 950L, 966L, 966L, 1005L, 1005L, 1005L, 1010L, 1010L, 1010L, 1013L, 1013L, 1013L, 1016L, 1016L, 1016L, 1045L, 1045L, 1045L, 1151L, 1151L, 1151L, 1201L, 1201L, 1201L, 1204L, 1204L, 1204L, 1244L, 1244L, 1244L, 1263L, 1263L, 1263L, 1269L, 1269L, 1269L, 1270L, 1270L, 1270L, 1308L, 1308L, 1308L, 1315L, 1315L, 1315L, 1393L, 1393L, 1439L, 1439L, 1441L, 1441L, 1441L, 1447L, 1447L, 1486L, 1486L, 1486L, 1520L, 1520L, 1545L, 1545L, 1545L, 1572L, 1572L, 1572L, 1575L, 1575L, 1580L, 1580L, 1580L, 1619L, 1619L, 1633L, 1633L, 1633L, 1687L, 1687L, 1687L, 1695L, 1695L, 1695L, 1728L, 1728L, 1728L, 1742L, 1742L, 1752L, 1752L, 1761L, 1761L, 1761L, 1807L, 1807L, 1807L, 1847L, 1847L, 1847L, 1861L, 1861L, 1866L, 1866L, 1866L, 1869L, 1869L, 1877L, 1877L, 1906L, 1906L, 1911L, 1911L, 1911L, 1981L, 1981L, 1981L, 2025L, 2025L, 2028L, 2028L, 2073L, 2073L, 2073L, 2097L, 2097L, 2141L, 2141L, 2141L, 2143L, 2143L, 2143L, 2173L, 2173L, 2173L, 2187L, 2187L, 2187L, 2199L, 2199L, 2218L, 2218L, 2218L, 2223L, 2223L, 2223L, 2263L, 2263L, 2263L, 2312L, 2312L, 2314L, 2314L, 2314L, 2366L, 2366L, 2366L, 2371L, 2371L, 2371L, 2435L, 2435L, 2435L, 2446L, 2446L, 2446L, 2448L, 2448L, 2598L, 2598L, 2598L, 2619L, 2619L, 2801L, 2801L, 2816L, 2816L, 2816L, 2817L, 2817L, 2817L, 2823L, 2823L, 2836L, 2836L, 2864L, 2864L, 2864L, 2865L, 2865L, 2865L, 2870L, 2870L, 2879L, 2879L, 2879L), `(state)` = c(1, 2, 3, 1, 1, 1, 1, 1, 1, 1, 2, 3, 1, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 3, 1, 3, 1, 1, 1, 2, 3, 1, 2, 2, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 3, 1, 3, 1, 1, 1, 2, 3, 1, 2, 2, 1, 2, 3, 1, 2, 3, 1, 2, 2, 1, 2, 3, 1, 2, 2, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 2, 1, 2, 3, 1, 2, 2, 1, 2, 2, 1, 3, 1, 3, 1, 2, 2, 1, 1, 1, 2, 3, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 3, 1, 3, 1, 2, 2, 1, 2, 3, 1, 2, 2, 1, 2, 2, 1, 3, 1, 1, 1, 2, 3, 1, 2, 2, 1, 2, 2, 1, 3, 1, 2, 2, 1, 3, 1, 3, 1, 3, 1, 2, 2, 1, 2, 2, 1, 1, 1, 1, 1, 2, 3, 1, 3, 1, 2, 2, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 1, 1, 2, 2, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 2, 1, 2, 3, 1, 2, 2, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 2, 3, 1, 2, 3, 1, 3, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 3), `(time)` = c(0, 2.42022603865082, 14.6202584741099, 0, 1.06335115169736, 0, 3.37846853071824, 0, 5.91722974553704, 0, 4.58288009058403, 9.52924055461131, 0, 6.05977787502578, 0, 5.11314795230023, 14.1889426135388, 0, 3.9793853225728, 9.98404531133461, 0, 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8.02066811347412, 15, 0, 4.50021161766982, 6.28881715788393, 0, 4.95045249025033, 0, 1.94473282188878, 0, 1.23358175813834, 3.81546577904373, 0, 2.45351897996223, 0, 5.75103343570654, 12.8507074011371, 0, 3.13150474335998, 0, 3.62361482018708, 15, 0, 1.70753057440278, 2.90423630503938, 0, 4.71622260985896, 0, 4.68820884543174, 10.6059529059576, 0, 5.67809275410179, 0, 5.74954350923768, 11.1949939368018, 0, 2.16842943591225, 9.5564392590454, 0, 4.11827209679337, 5.9958520391956, 0, 6.26891657464451, 11.293289180075, 0, 3.89833941377084, 0, 2.06416486447456, 0, 4.41538331020301, 10.4442594197434, 0, 5.51281272877163, 9.3304296140559, 0, 14.5558520209811, 15, 0, 3.96473119041544, 0, 6.82327246979789, 15, 0, 6.62903601714705, 0, 7.15516451563556, 0, 3.99949697666245, 0, 5.92132857335279, 8.07890239404514, 0, 5.72167968614231, 9.83430769527331, 0, 1.7716667172499, 0, 5.90151765849441, 0, 4.48052619859954, 12.8467609089349, 0, 3.71839352901634, 0, 4.42204647988183, 13.1059182373277, 0, 0.645748993758942, 5.43988305911687, 0, 2.22858722279899, 11.2371628721608, 0, 6.74261799564098, 10.4231144904582, 0, 0.588790811598301, 0, 6.71063269816809, 15, 0, 1.69891210470069, 7.27827564580366, 0, 6.63979810625763, 9.28839638130739, 0, 0.3010408510454, 0, 11.7159918790512, 15, 0, 7.42690194298182, 13.4159356094477, 0, 7.50595106923712, 15, 0, 10.496191308296, 10.8230564317884, 0, 0.503689229919938, 3.92409760504961, 0, 1.68466971058728, 0, 10.394417598933, 15, 0, 0.167301606852561, 0, 5.043442575261, 0, 4.30473713445075, 13.5908252629751, 0, 5.52245333077557, 13.1322277836806, 0, 6.52321177528359, 0, 4.89751752465963, 0, 4.06238924789648, 12.5009299948098, 0, 6.76183990406097, 15, 0, 0.463039907882884, 0, 3.19690445223537, 13.2164889044032 ), `(obstype)` = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), `(obstrue)` = c(1, 2, 3, 1, 1, 1, 1, 1, 1, 1, 2, 3, 1, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 3, 1, 3, 1, 1, 1, 2, 3, 1, 2, 2, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 3, 1, 3, 1, 1, 1, 2, 3, 1, 2, 2, 1, 2, 3, 1, 2, 3, 1, 2, 2, 1, 2, 3, 1, 2, 2, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 2, 1, 2, 3, 1, 2, 2, 1, 2, 2, 1, 3, 1, 3, 1, 2, 2, 1, 1, 1, 2, 3, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 3, 1, 3, 1, 2, 2, 1, 2, 3, 1, 2, 2, 1, 2, 2, 1, 3, 1, 1, 1, 2, 3, 1, 2, 2, 1, 2, 2, 1, 3, 1, 2, 2, 1, 3, 1, 3, 1, 3, 1, 2, 2, 1, 2, 2, 1, 1, 1, 1, 1, 2, 3, 1, 3, 1, 2, 2, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 1, 1, 2, 2, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 2, 1, 2, 3, 1, 2, 2, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 2, 3, 1, 2, 3, 1, 3, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 3), `(obs)` = 1:256, `(pcomb)` = c(NA, 1L, 2L, NA, 3L, NA, 4L, NA, 5L, NA, 6L, 7L, NA, 8L, NA, 9L, 10L, NA, 11L, 12L, NA, 13L, 14L, NA, 15L, NA, 16L, NA, 17L, NA, 18L, 19L, NA, 20L, 21L, NA, 22L, 23L, NA, 24L, 25L, NA, 26L, NA, 27L, 28L, NA, 29L, 30L, NA, 31L, NA, 32L, 33L, NA, 34L, 35L, NA, 36L, NA, 37L, 38L, NA, 39L, NA, 40L, NA, 41L, 42L, NA, 43L, 44L, NA, 45L, 46L, NA, 47L, 48L, NA, 49L, 50L, NA, 51L, 52L, NA, 53L, 54L, NA, 55L, 56L, NA, 57L, 58L, NA, 59L, 60L, NA, 61L, 62L, NA, 63L, 64L, NA, 65L, 66L, NA, 67L, 68L, NA, 69L, NA, 70L, NA, 71L, 72L, NA, 73L, NA, 74L, 75L, NA, 76L, NA, 77L, 78L, NA, 79L, 80L, NA, 81L, NA, 82L, 83L, NA, 84L, NA, 85L, 86L, NA, 87L, 88L, NA, 89L, 90L, NA, 91L, 92L, NA, 93L, NA, 94L, NA, 95L, 96L, NA, 97L, 98L, NA, 99L, 100L, NA, 101L, NA, 102L, 103L, NA, 104L, NA, 105L, NA, 106L, NA, 107L, 108L, NA, 109L, 110L, NA, 111L, NA, 112L, NA, 113L, 114L, NA, 115L, NA, 116L, 117L, NA, 118L, 119L, NA, 120L, 121L, NA, 122L, 123L, NA, 124L, NA, 125L, 126L, NA, 127L, 128L, NA, 129L, 130L, NA, 131L, NA, 132L, 133L, NA, 134L, 135L, NA, 136L, 137L, NA, 138L, 139L, NA, 140L, 141L, NA, 142L, NA, 143L, 144L, NA, 145L, NA, 146L, NA, 147L, 148L, NA, 149L, 150L, NA, 151L, NA, 152L, NA, 153L, 154L, NA, 155L, 156L, NA, 157L, NA, 158L, 159L)), mf.agg = list(strategy_name = c(2L, 3L, 1L, 1L, 3L, 3L, 1L, 2L, 1L, 2L, 3L, 1L, 3L, 2L, 3L, 3L, 2L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 1L, 3L, 1L, 2L, 3L, 1L, 3L, 2L, 2L, 3L, 3L, 1L, 1L, 1L, 3L, 1L, 2L, 1L, 2L, 3L, 3L, 2L, 3L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 1L, 2L, 2L, 2L, 3L, 1L, 3L, 2L, 1L, 1L, 3L, 2L, 3L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 3L, 3L, 1L, 3L, 2L, 3L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 1L, 2L, 2L, 3L, 2L, 2L, 2L, 2L, 3L, 1L, 1L, 2L, 3L, 1L, 3L, 1L, 2L, 1L, 2L, 2L, 1L, 3L, 2L, 2L, 3L, 2L, 3L, 1L, 2L, 2L, 1L, 2L, 3L, 3L, 3L, 1L, 1L, 1L, 3L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 3L, 3L, 2L, 1L, 2L, 2L, 1L, 1L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 2L, 3L, 1L, 3L, 3L), `(subject)` = c(2619L, 2312L, 2435L, 677L, 1847L, 2870L, 2446L, 2199L, 2143L, 966L, 1045L, 127L, 1572L, 1441L, 1151L, 2448L, 829L, 2223L, 1572L, 2025L, 1315L, 440L, 528L, 1695L, 890L, 1439L, 1201L, 2879L, 2598L, 2435L, 1151L, 1545L, 2314L, 1L, 1847L, 1752L, 1244L, 1911L, 1687L, 2173L, 507L, 569L, 500L, 1L, 1447L, 1441L, 678L, 2263L, 787L, 1204L, 1520L, 2879L, 507L, 2314L, 209L, 2446L, 1263L, 1545L, 2187L, 2097L, 787L, 1005L, 1807L, 1201L, 1742L, 1861L, 378L, 1906L, 2864L, 1981L, 1695L, 905L, 2816L, 1761L, 2141L, 2073L, 1315L, 1013L, 267L, 2598L, 1580L, 1575L, 2143L, 2836L, 905L, 267L, 1393L, 569L, 1728L, 2801L, 528L, 827L, 285L, 1204L, 488L, 829L, 1633L, 1269L, 1010L, 1807L, 2817L, 2223L, 1016L, 1619L, 1981L, 1633L, 1486L, 2028L, 250L, 1580L, 1911L, 2366L, 378L, 1761L, 280L, 1728L, 2823L, 1270L, 1269L, 1869L, 2263L, 2218L, 2187L, 2865L, 1866L, 1270L, 1308L, 612L, 860L, 1486L, 1877L, 1687L, 2366L, 2371L, 2371L, 2817L, 1016L, 1010L, 860L, 612L, 1308L, 1866L, 2865L, 478L, 2218L, 2073L, 2864L, 1013L, 2141L, 950L, 1005L, 2173L, 1263L, 285L, 2816L, 1045L, 1244L, 440L, 678L), `(fromstate)` = c(1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 2, 2, 1, 1, 2, 2, 1, 2, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 2, 2, 2, 2, 2, 1, 1, 1, 2, 1, 2, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 2, 1, 2, 2, 1, 2, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 2, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2, 1, 2, 1, 2, 1, 2, 2, 2, 2, 1, 1, 2, 2, 1, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 1, 2, 2, 1), `(time)` = c(0, 0, 10.496191308296, 0, 14.5558520209811, 0, 0, 0, 0, 0, 9.6100249037167, 0, 1.70753057440278, 0, 0, 0, 0, 0, 0, 0, 4.50021161766982, 0, 0, 4.11827209679337, 0, 0, 3.88422755035061, 3.19690445223537, 0, 0, 1.60594620632657, 3.62361482018708, 0, 2.42022603865082, 0, 0, 0, 5.92132857335279, 0, 0, 3.27374095025703, 0, 0, 0, 0, 1.23358175813834, 9.97610073141581, 6.63979810625763, 3.75908505063792, 5.19510834409654, 0, 0, 0, 11.7159918790512, 0, 0.503689229919938, 0, 0, 6.74261799564098, 0, 0, 0, 5.51281272877163, 0, 0, 0, 0, 0, 0, 5.72167968614231, 0, 4.90076951101563, 0, 0, 0, 0, 0, 0, 0, 10.394417598933, 0, 0, 0.645748993758942, 0, 0, 4.58288009058403, 0, 2.32244494219243, 6.26891657464451, 0, 1.83614749739054, 0, 0, 0, 0, 1.69717255488757, 5.74954350923768, 0, 0, 0, 0, 1.69891210470069, 0, 0, 0, 0, 0, 0, 0, 4.68820884543174, 0, 7.42690194298182, 3.9793853225728, 4.41538331020301, 0, 0, 0, 6.88192152582238, 5.44870446876656, 0, 0, 0, 0, 0, 0, 0, 8.02066811347412, 7.99197312290447, 0, 5.75103343570654, 0, 2.16842943591225, 0, 7.50595106923712, 0, 5.52245333077557, 5.63132673670023, 5.4803828995153, 7.06069513880918, 0, 0, 6.82327246979789, 6.76183990406097, 0, 6.71063269816809, 4.48052619859954, 4.06238924789648, 4.57313999656492, 4.42204647988183, 0, 3.76012797928306, 2.22858722279899, 3.43228499180158, 5.11314795230023, 4.30473713445075, 0, 2.15403129570777, 1.82958139332304, 0), `(obstype)` = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), `(obstrue)` = c(1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 2, 2, 1, 1, 2, 2, 1, 2, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 2, 2, 2, 2, 2, 1, 1, 1, 2, 1, 2, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 2, 1, 2, 2, 1, 2, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 2, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2, 1, 2, 1, 2, 1, 2, 2, 2, 2, 1, 1, 2, 2, 1, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 1, 2, 2, 1), `(obs)` = c(233L, 211L, 223L, 43L, 160L, 253L, 225L, 200L, 191L, 66L, 81L, 5L, 128L, 114L, 83L, 228L, 53L, 205L, 127L, 179L, 108L, 22L, 34L, 144L, 59L, 112L, 87L, 256L, 230L, 222L, 84L, 125L, 213L, 3L, 159L, 151L, 92L, 174L, 140L, 194L, 32L, 37L, 29L, 2L, 117L, 115L, 46L, 209L, 49L, 90L, 122L, 255L, 31L, 214L, 7L, 226L, 95L, 124L, 198L, 186L, 48L, 68L, 157L, 86L, 149L, 162L, 19L, 171L, 247L, 177L, 143L, 62L, 237L, 153L, 188L, 183L, 107L, 74L, 11L, 231L, 132L, 130L, 192L, 245L, 61L, 12L, 110L, 38L, 147L, 235L, 35L, 51L, 16L, 89L, 27L, 54L, 138L, 98L, 71L, 156L, 240L, 206L, 77L, 135L, 176L, 137L, 119L, 181L, 9L, 133L, 173L, 217L, 20L, 154L, 14L, 146L, 243L, 102L, 99L, 167L, 208L, 202L, 197L, 250L, 164L, 101L, 105L, 41L, 56L, 120L, 169L, 141L, 216L, 220L, 219L, 241L, 78L, 72L, 57L, 40L, 104L, 165L, 251L, 25L, 203L, 184L, 248L, 75L, 189L, 64L, 69L, 195L, 96L, 17L, 238L, 80L, 93L, 23L, 45L), `(tostate)` = c(1, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 2, 2, 1, 2, 2, 2, 1, 2, 2, 2, 2, 1, 3, 2, 3, 2, 2, 3, 2, 2, 3, 2, 1, 2, 2, 2, 2, 3, 2, 1, 2, 1, 2, 2, 2, 2, 3, 1, 2, 2, 2, 1, 2, 2, 2, 3, 3, 2, 2, 2, 2, 3, 3, 2, 3, 2, 2, 2, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 3, 1, 2, 3, 3, 2, 2, 1, 2, 1, 2, 2, 3, 2, 2, 2, 2, 2, 2, 2, 2, 3, 2, 2, 2, 1, 1, 3, 2, 3, 3, 3, 3, 2, 3, 3, 2, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 2, 2, 2, 3, 3, 2, 2, 2, 2, 2, 2, 3, 2, 3, 2, 3, 2, 3, 3, 3, 3, 3, 3, 2, 3, 3, 2), `(timelag)` = c(0.167301606852561, 0.3010408510454, 0.326865123492345, 0.373379818629473, 0.444147979018943, 0.463039907882884, 0.503689229919938, 0.588790811598301, 0.645748993758942, 0.777970170602202, 0.993271194635708, 1.06335115169736, 1.19670573063659, 1.23358175813834, 1.60594620632657, 1.68466971058728, 1.69717255488757, 1.69891210470069, 1.70753057440278, 1.7716667172499, 1.78860554021411, 1.82958139332304, 1.83614749739054, 1.87757994240222, 1.8811577023007, 1.94473282188878, 1.99262343138036, 10.0195844521678, 10.394417598933, 10.496191308296, 10.8717317382293, 11.3763851798129, 11.7159918790512, 12.2000324354591, 14.5558520209811, 2.06416486447456, 2.15403129570777, 2.15757382069236, 2.16842943591225, 2.22858722279899, 2.26286172221628, 2.32244494219243, 2.40431244601521, 2.42022603865082, 2.45351897996223, 2.58188402090539, 2.64508501492929, 2.64859827504976, 2.75559795196811, 2.86082431740821, 3.13150474335998, 3.19690445223537, 3.27374095025703, 3.28400812094883, 3.37846853071824, 3.42040837512967, 3.43228499180158, 3.62361482018708, 3.68049649481719, 3.71839352901634, 3.75908505063792, 3.76012797928306, 3.81761688528427, 3.88422755035061, 3.89833941377084, 3.96473119041544, 3.9793853225728, 3.99949697666245, 4.06238924789648, 4.112628009131, 4.11827209679337, 4.30226044417887, 4.30473713445075, 4.41538331020301, 4.42204647988183, 4.48052619859954, 4.50021161766982, 4.57313999656492, 4.58288009058403, 4.60558240106704, 4.68820884543174, 4.71622260985896, 4.79413406535793, 4.89751752465963, 4.90076951101563, 4.94636046402728, 4.95045249025033, 4.9800215676713, 5.02437260543045, 5.043442575261, 5.04588780647037, 5.07091985782608, 5.11314795230023, 5.19510834409654, 5.28795059607339, 5.31591291099067, 5.44545042756416, 5.44870446876656, 5.4803828995153, 5.51281272877163, 5.52245333077557, 5.57936354110297, 5.63132673670023, 5.67809275410179, 5.72167968614231, 5.74954350923768, 5.75103343570654, 5.90151765849441, 5.91722974553704, 5.91774406052587, 5.92132857335279, 5.98903366646586, 6.00465998876181, 6.02887610954037, 6.05977787502578, 6.26891657464451, 6.52321177528359, 6.57332214653931, 6.61657927985586, 6.62903601714705, 6.63979810625763, 6.71063269816809, 6.74261799564098, 6.76183990406097, 6.82327246979789, 6.88192152582238, 6.97933188652588, 7.00802687709553, 7.06069513880918, 7.09967396543056, 7.15516451563556, 7.38800982313315, 7.42690194298182, 7.49404893076288, 7.50595106923712, 7.60977445290499, 7.706898070744, 7.71585734599353, 7.93930486119082, 7.99197312290447, 8.02066811347412, 8.17672753020211, 8.23816009593903, 8.25267813210891, 8.28936730183191, 8.36623471033537, 8.43854074691333, 8.51141085915261, 8.68387175744583, 8.91516227995197, 8.99403132866118, 9.00857564936184, 9.03136899667618, 9.07579466123855, 9.2860881285244, 9.6100249037167, 9.66122281910707, 9.88689985140138, 9.97610073141581), `(nocc)` = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 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-0.314465408805031, 0.685534591194969, 0.685534591194969, -0.314465408805031, -0.314465408805031, -0.314465408805031, -0.314465408805031, -0.314465408805031, -0.314465408805031, 0.685534591194969, -0.314465408805031, -0.314465408805031, 0.685534591194969, -0.314465408805031, -0.314465408805031, 0.685534591194969, -0.314465408805031, 0.685534591194969, -0.314465408805031, 0.685534591194969, 0.685534591194969), mm.mcov = NULL, mm.hcov = NULL, mm.icov = NULL, subject.weights = NULL), qmodel = list(nstates = 3L, iso = 4, perm = c(1, 2, 3), qperm = 1:3, npars = 3, imatrix = c(0, 0, 0, 1, 0, 0, 1, 1, 0), qmatrix = c(-0.29402, 0, 0, 0.28163, -0.10204, 0, 0.01239, 0.10204, 0), inits = c(0.28163, 0.01239, 0.10204), constr = 1:3, ndpars = 3L, expm = 1), qcmodel = list( npars = 6, ndpars = 6, ncovs = 2, constr = c(1, 2, 3, 4, 5, 6), covlabels = c("strategy_nameNew 1", "strategy_nameNew 2" ), inits = c(0, 0, 0, 0, 0, 0), covmeans = c(`strategy_nameNew 1` = 0.352201257861635, `strategy_nameNew 2` = 0.314465408805031), cri = c(1, 0, 0, 1, 0, 0)), cmodel = list(ncens = 0, censor = NULL, states = NULL, states_list = NULL, index = NULL), hmodel = list(hidden = FALSE, models = c(0, 0, 0), nipars = 0, nicoveffs = 0, totpars = 0, ncoveffs = 0, ematrix = FALSE))
7: do.call(optfn, args)
8: msm.optim(opt.method, p, hessian, use.deriv, msmdata, qmodel, qcmodel, cmodel, hmodel, ...)
9: msm(state_id ~ time, subject = patient_id, data = onc3p[patient_id %in% sample(patient_id, 100)], covariates = list(`1-2` = ~strategy_name), qmatrix = qinit)
An irrecoverable exception occurred. R is aborting now ...
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 0.5.5
Check: tests
Result: ERROR
Running ‘testthat.R’ [39s/68s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(hesim)
>
> test_check("hesim")
sample = 1
sample = 2
*** caught segfault ***
address 0x1, cause 'memory not mapped'
Traceback:
1: Ccall.msm(params, do.what = "lik", ...)
2: fn(par, ...)
3: (function (par) fn(par, ...))(c(qbase = -1.26716112628169, qbase = -4.39086558334109, qbase = -2.28239038570853, qcov = 0, qcov = 0))
4: optim(method = "BFGS", control = list(), par = c(qbase = -1.26716112628169, qbase = -4.39086558334109, qbase = -2.28239038570853, qcov = 0, qcov = 0), fn = function (params, ...) { assign("nliks", get("nliks", msm.globals) + 1, envir = msm.globals) args <- list(...) w <- args$msmdata$subject.weights if (!is.null(w)) { lik <- Ccall.msm(params, do.what = "lik.subj", ...) sum(w * lik) } else Ccall.msm(params, do.what = "lik", ...)}, hessian = TRUE, gr = function (params, ...) { w <- list(...)$msmdata$subject.weights if (!is.null(w)) { deriv <- Ccall.msm(params, do.what = "deriv.subj", ...) apply(w * deriv, 2, sum) } else Ccall.msm(params, do.what = "deriv", ...)}, msmdata = list(mf = list(strategy_name = c(3L, 3L, 3L, 1L, 1L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 3L, 3L, 3L, 1L, 1L, 3L, 3L, 3L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 2L, 2L, 2L, 3L, 3L, 3L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 3L, 3L, 2L, 2L, 2L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 3L, 3L, 1L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 1L, 1L, 1L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 2L, 2L, 2L), `(subject)` = c(1L, 1L, 1L, 127L, 127L, 209L, 209L, 250L, 250L, 267L, 267L, 267L, 280L, 280L, 285L, 285L, 285L, 378L, 378L, 378L, 440L, 440L, 440L, 478L, 478L, 488L, 488L, 500L, 500L, 507L, 507L, 507L, 528L, 528L, 528L, 569L, 569L, 569L, 612L, 612L, 612L, 677L, 677L, 678L, 678L, 678L, 787L, 787L, 787L, 827L, 827L, 829L, 829L, 829L, 860L, 860L, 860L, 890L, 890L, 905L, 905L, 905L, 950L, 950L, 966L, 966L, 1005L, 1005L, 1005L, 1010L, 1010L, 1010L, 1013L, 1013L, 1013L, 1016L, 1016L, 1016L, 1045L, 1045L, 1045L, 1151L, 1151L, 1151L, 1201L, 1201L, 1201L, 1204L, 1204L, 1204L, 1244L, 1244L, 1244L, 1263L, 1263L, 1263L, 1269L, 1269L, 1269L, 1270L, 1270L, 1270L, 1308L, 1308L, 1308L, 1315L, 1315L, 1315L, 1393L, 1393L, 1439L, 1439L, 1441L, 1441L, 1441L, 1447L, 1447L, 1486L, 1486L, 1486L, 1520L, 1520L, 1545L, 1545L, 1545L, 1572L, 1572L, 1572L, 1575L, 1575L, 1580L, 1580L, 1580L, 1619L, 1619L, 1633L, 1633L, 1633L, 1687L, 1687L, 1687L, 1695L, 1695L, 1695L, 1728L, 1728L, 1728L, 1742L, 1742L, 1752L, 1752L, 1761L, 1761L, 1761L, 1807L, 1807L, 1807L, 1847L, 1847L, 1847L, 1861L, 1861L, 1866L, 1866L, 1866L, 1869L, 1869L, 1877L, 1877L, 1906L, 1906L, 1911L, 1911L, 1911L, 1981L, 1981L, 1981L, 2025L, 2025L, 2028L, 2028L, 2073L, 2073L, 2073L, 2097L, 2097L, 2141L, 2141L, 2141L, 2143L, 2143L, 2143L, 2173L, 2173L, 2173L, 2187L, 2187L, 2187L, 2199L, 2199L, 2218L, 2218L, 2218L, 2223L, 2223L, 2223L, 2263L, 2263L, 2263L, 2312L, 2312L, 2314L, 2314L, 2314L, 2366L, 2366L, 2366L, 2371L, 2371L, 2371L, 2435L, 2435L, 2435L, 2446L, 2446L, 2446L, 2448L, 2448L, 2598L, 2598L, 2598L, 2619L, 2619L, 2801L, 2801L, 2816L, 2816L, 2816L, 2817L, 2817L, 2817L, 2823L, 2823L, 2836L, 2836L, 2864L, 2864L, 2864L, 2865L, 2865L, 2865L, 2870L, 2870L, 2879L, 2879L, 2879L), `(state)` = c(1, 2, 3, 1, 1, 1, 1, 1, 1, 1, 2, 3, 1, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 3, 1, 3, 1, 1, 1, 2, 3, 1, 2, 2, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 3, 1, 3, 1, 1, 1, 2, 3, 1, 2, 2, 1, 2, 3, 1, 2, 3, 1, 2, 2, 1, 2, 3, 1, 2, 2, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 2, 1, 2, 3, 1, 2, 2, 1, 2, 2, 1, 3, 1, 3, 1, 2, 2, 1, 1, 1, 2, 3, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 3, 1, 3, 1, 2, 2, 1, 2, 3, 1, 2, 2, 1, 2, 2, 1, 3, 1, 1, 1, 2, 3, 1, 2, 2, 1, 2, 2, 1, 3, 1, 2, 2, 1, 3, 1, 3, 1, 3, 1, 2, 2, 1, 2, 2, 1, 1, 1, 1, 1, 2, 3, 1, 3, 1, 2, 2, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 1, 1, 2, 2, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 2, 1, 2, 3, 1, 2, 2, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 2, 3, 1, 2, 3, 1, 3, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 3), `(time)` = c(0, 2.42022603865082, 14.6202584741099, 0, 1.06335115169736, 0, 3.37846853071824, 0, 5.91722974553704, 0, 4.58288009058403, 9.52924055461131, 0, 6.05977787502578, 0, 5.11314795230023, 14.1889426135388, 0, 3.9793853225728, 9.98404531133461, 0, 1.82958139332304, 11.7164812447244, 0, 8.25267813210891, 0, 5.28795059607339, 0, 2.40431244601521, 0, 3.27374095025703, 5.53660267247331, 0, 1.83614749739054, 6.8820353038609, 0, 2.32244494219243, 7.30246650986373, 0, 7.99197312290447, 15, 0, 0.373379818629473, 0, 9.97610073141581, 12.6211857463451, 0, 3.75908505063792, 6.51468300260603, 0, 5.07091985782608, 0, 1.69717255488757, 7.01308546587825, 0, 7.06069513880918, 15, 0, 1.8811577023007, 0, 4.90076951101563, 9.2030299551945, 0, 8.91516227995197, 0, 0.777970170602202, 0, 3.76012797928306, 12.7541593079442, 0, 5.4803828995153, 13.1962402455088, 0, 4.57313999656492, 13.0845508557175, 0, 5.63132673670023, 13.3382248074442, 0, 9.6100249037167, 10.6032960983524, 0, 1.60594620632657, 12.4776779445559, 0, 3.88422755035061, 5.87685098173097, 0, 5.19510834409654, 8.05593266150475, 0, 2.15403129570777, 11.8152541148148, 0, 3.43228499180158, 12.4636539884778, 0, 5.44870446876656, 12.0652837486224, 0, 6.88192152582238, 13.4552436723617, 0, 8.02066811347412, 15, 0, 4.50021161766982, 6.28881715788393, 0, 4.95045249025033, 0, 1.94473282188878, 0, 1.23358175813834, 3.81546577904373, 0, 2.45351897996223, 0, 5.75103343570654, 12.8507074011371, 0, 3.13150474335998, 0, 3.62361482018708, 15, 0, 1.70753057440278, 2.90423630503938, 0, 4.71622260985896, 0, 4.68820884543174, 10.6059529059576, 0, 5.67809275410179, 0, 5.74954350923768, 11.1949939368018, 0, 2.16842943591225, 9.5564392590454, 0, 4.11827209679337, 5.9958520391956, 0, 6.26891657464451, 11.293289180075, 0, 3.89833941377084, 0, 2.06416486447456, 0, 4.41538331020301, 10.4442594197434, 0, 5.51281272877163, 9.3304296140559, 0, 14.5558520209811, 15, 0, 3.96473119041544, 0, 6.82327246979789, 15, 0, 6.62903601714705, 0, 7.15516451563556, 0, 3.99949697666245, 0, 5.92132857335279, 8.07890239404514, 0, 5.72167968614231, 9.83430769527331, 0, 1.7716667172499, 0, 5.90151765849441, 0, 4.48052619859954, 12.8467609089349, 0, 3.71839352901634, 0, 4.42204647988183, 13.1059182373277, 0, 0.645748993758942, 5.43988305911687, 0, 2.22858722279899, 11.2371628721608, 0, 6.74261799564098, 10.4231144904582, 0, 0.588790811598301, 0, 6.71063269816809, 15, 0, 1.69891210470069, 7.27827564580366, 0, 6.63979810625763, 9.28839638130739, 0, 0.3010408510454, 0, 11.7159918790512, 15, 0, 7.42690194298182, 13.4159356094477, 0, 7.50595106923712, 15, 0, 10.496191308296, 10.8230564317884, 0, 0.503689229919938, 3.92409760504961, 0, 1.68466971058728, 0, 10.394417598933, 15, 0, 0.167301606852561, 0, 5.043442575261, 0, 4.30473713445075, 13.5908252629751, 0, 5.52245333077557, 13.1322277836806, 0, 6.52321177528359, 0, 4.89751752465963, 0, 4.06238924789648, 12.5009299948098, 0, 6.76183990406097, 15, 0, 0.463039907882884, 0, 3.19690445223537, 13.2164889044032), `(obstype)` = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), `(obstrue)` = c(1, 2, 3, 1, 1, 1, 1, 1, 1, 1, 2, 3, 1, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 3, 1, 3, 1, 1, 1, 2, 3, 1, 2, 2, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 3, 1, 3, 1, 1, 1, 2, 3, 1, 2, 2, 1, 2, 3, 1, 2, 3, 1, 2, 2, 1, 2, 3, 1, 2, 2, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 2, 1, 2, 3, 1, 2, 2, 1, 2, 2, 1, 3, 1, 3, 1, 2, 2, 1, 1, 1, 2, 3, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 3, 1, 3, 1, 2, 2, 1, 2, 3, 1, 2, 2, 1, 2, 2, 1, 3, 1, 1, 1, 2, 3, 1, 2, 2, 1, 2, 2, 1, 3, 1, 2, 2, 1, 3, 1, 3, 1, 3, 1, 2, 2, 1, 2, 2, 1, 1, 1, 1, 1, 2, 3, 1, 3, 1, 2, 2, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 1, 1, 2, 2, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 2, 1, 2, 3, 1, 2, 2, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 2, 3, 1, 2, 3, 1, 3, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 3), `(obs)` = 1:256, `(pcomb)` = c(NA, 1L, 2L, NA, 3L, NA, 4L, NA, 5L, NA, 6L, 7L, NA, 8L, NA, 9L, 10L, NA, 11L, 12L, NA, 13L, 14L, NA, 15L, NA, 16L, NA, 17L, NA, 18L, 19L, NA, 20L, 21L, NA, 22L, 23L, NA, 24L, 25L, NA, 26L, NA, 27L, 28L, NA, 29L, 30L, NA, 31L, NA, 32L, 33L, NA, 34L, 35L, NA, 36L, NA, 37L, 38L, NA, 39L, NA, 40L, NA, 41L, 42L, NA, 43L, 44L, NA, 45L, 46L, NA, 47L, 48L, NA, 49L, 50L, NA, 51L, 52L, NA, 53L, 54L, NA, 55L, 56L, NA, 57L, 58L, NA, 59L, 60L, NA, 61L, 62L, NA, 63L, 64L, NA, 65L, 66L, NA, 67L, 68L, NA, 69L, NA, 70L, NA, 71L, 72L, NA, 73L, NA, 74L, 75L, NA, 76L, NA, 77L, 78L, NA, 79L, 80L, NA, 81L, NA, 82L, 83L, NA, 84L, NA, 85L, 86L, NA, 87L, 88L, NA, 89L, 90L, NA, 91L, 92L, NA, 93L, NA, 94L, NA, 95L, 96L, NA, 97L, 98L, NA, 99L, 100L, NA, 101L, NA, 102L, 103L, NA, 104L, NA, 105L, NA, 106L, NA, 107L, 108L, NA, 109L, 110L, NA, 111L, NA, 112L, NA, 113L, 114L, NA, 115L, NA, 116L, 117L, NA, 118L, 119L, NA, 120L, 121L, NA, 122L, 123L, NA, 124L, NA, 125L, 126L, NA, 127L, 128L, NA, 129L, 130L, NA, 131L, NA, 132L, 133L, NA, 134L, 135L, NA, 136L, 137L, NA, 138L, 139L, NA, 140L, 141L, NA, 142L, NA, 143L, 144L, NA, 145L, NA, 146L, NA, 147L, 148L, NA, 149L, 150L, NA, 151L, NA, 152L, NA, 153L, 154L, NA, 155L, 156L, NA, 157L, NA, 158L, 159L)), mf.agg = list(strategy_name = c(2L, 3L, 1L, 1L, 3L, 3L, 1L, 2L, 1L, 2L, 3L, 1L, 3L, 2L, 3L, 3L, 2L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 1L, 3L, 1L, 2L, 3L, 1L, 3L, 2L, 2L, 3L, 3L, 1L, 1L, 1L, 3L, 1L, 2L, 1L, 2L, 3L, 3L, 2L, 3L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 1L, 2L, 2L, 2L, 3L, 1L, 3L, 2L, 1L, 1L, 3L, 2L, 3L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 3L, 3L, 1L, 3L, 2L, 3L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 1L, 2L, 2L, 3L, 2L, 2L, 2L, 2L, 3L, 1L, 1L, 2L, 3L, 1L, 3L, 1L, 2L, 1L, 2L, 2L, 1L, 3L, 2L, 2L, 3L, 2L, 3L, 1L, 2L, 2L, 1L, 2L, 3L, 3L, 3L, 1L, 1L, 1L, 3L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 3L, 3L, 2L, 1L, 2L, 2L, 1L, 1L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 2L, 3L, 1L, 3L, 3L), `(subject)` = c(2619L, 2312L, 2435L, 677L, 1847L, 2870L, 2446L, 2199L, 2143L, 966L, 1045L, 127L, 1572L, 1441L, 1151L, 2448L, 829L, 2223L, 1572L, 2025L, 1315L, 440L, 528L, 1695L, 890L, 1439L, 1201L, 2879L, 2598L, 2435L, 1151L, 1545L, 2314L, 1L, 1847L, 1752L, 1244L, 1911L, 1687L, 2173L, 507L, 569L, 500L, 1L, 1447L, 1441L, 678L, 2263L, 787L, 1204L, 1520L, 2879L, 507L, 2314L, 209L, 2446L, 1263L, 1545L, 2187L, 2097L, 787L, 1005L, 1807L, 1201L, 1742L, 1861L, 378L, 1906L, 2864L, 1981L, 1695L, 905L, 2816L, 1761L, 2141L, 2073L, 1315L, 1013L, 267L, 2598L, 1580L, 1575L, 2143L, 2836L, 905L, 267L, 1393L, 569L, 1728L, 2801L, 528L, 827L, 285L, 1204L, 488L, 829L, 1633L, 1269L, 1010L, 1807L, 2817L, 2223L, 1016L, 1619L, 1981L, 1633L, 1486L, 2028L, 250L, 1580L, 1911L, 2366L, 378L, 1761L, 280L, 1728L, 2823L, 1270L, 1269L, 1869L, 2263L, 2218L, 2187L, 2865L, 1866L, 1270L, 1308L, 612L, 860L, 1486L, 1877L, 1687L, 2366L, 2371L, 2371L, 2817L, 1016L, 1010L, 860L, 612L, 1308L, 1866L, 2865L, 478L, 2218L, 2073L, 2864L, 1013L, 2141L, 950L, 1005L, 2173L, 1263L, 285L, 2816L, 1045L, 1244L, 440L, 678L), `(fromstate)` = c(1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 2, 2, 1, 1, 2, 2, 1, 2, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 2, 2, 2, 2, 2, 1, 1, 1, 2, 1, 2, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 2, 1, 2, 2, 1, 2, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 2, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2, 1, 2, 1, 2, 1, 2, 2, 2, 2, 1, 1, 2, 2, 1, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 1, 2, 2, 1), `(time)` = c(0, 0, 10.496191308296, 0, 14.5558520209811, 0, 0, 0, 0, 0, 9.6100249037167, 0, 1.70753057440278, 0, 0, 0, 0, 0, 0, 0, 4.50021161766982, 0, 0, 4.11827209679337, 0, 0, 3.88422755035061, 3.19690445223537, 0, 0, 1.60594620632657, 3.62361482018708, 0, 2.42022603865082, 0, 0, 0, 5.92132857335279, 0, 0, 3.27374095025703, 0, 0, 0, 0, 1.23358175813834, 9.97610073141581, 6.63979810625763, 3.75908505063792, 5.19510834409654, 0, 0, 0, 11.7159918790512, 0, 0.503689229919938, 0, 0, 6.74261799564098, 0, 0, 0, 5.51281272877163, 0, 0, 0, 0, 0, 0, 5.72167968614231, 0, 4.90076951101563, 0, 0, 0, 0, 0, 0, 0, 10.394417598933, 0, 0, 0.645748993758942, 0, 0, 4.58288009058403, 0, 2.32244494219243, 6.26891657464451, 0, 1.83614749739054, 0, 0, 0, 0, 1.69717255488757, 5.74954350923768, 0, 0, 0, 0, 1.69891210470069, 0, 0, 0, 0, 0, 0, 0, 4.68820884543174, 0, 7.42690194298182, 3.9793853225728, 4.41538331020301, 0, 0, 0, 6.88192152582238, 5.44870446876656, 0, 0, 0, 0, 0, 0, 0, 8.02066811347412, 7.99197312290447, 0, 5.75103343570654, 0, 2.16842943591225, 0, 7.50595106923712, 0, 5.52245333077557, 5.63132673670023, 5.4803828995153, 7.06069513880918, 0, 0, 6.82327246979789, 6.76183990406097, 0, 6.71063269816809, 4.48052619859954, 4.06238924789648, 4.57313999656492, 4.42204647988183, 0, 3.76012797928306, 2.22858722279899, 3.43228499180158, 5.11314795230023, 4.30473713445075, 0, 2.15403129570777, 1.82958139332304, 0), `(obstype)` = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), `(obstrue)` = c(1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 2, 2, 1, 1, 2, 2, 1, 2, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 2, 2, 2, 2, 2, 1, 1, 1, 2, 1, 2, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 2, 1, 2, 2, 1, 2, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 2, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2, 1, 2, 1, 2, 1, 2, 2, 2, 2, 1, 1, 2, 2, 1, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 1, 2, 2, 1), `(obs)` = c(233L, 211L, 223L, 43L, 160L, 253L, 225L, 200L, 191L, 66L, 81L, 5L, 128L, 114L, 83L, 228L, 53L, 205L, 127L, 179L, 108L, 22L, 34L, 144L, 59L, 112L, 87L, 256L, 230L, 222L, 84L, 125L, 213L, 3L, 159L, 151L, 92L, 174L, 140L, 194L, 32L, 37L, 29L, 2L, 117L, 115L, 46L, 209L, 49L, 90L, 122L, 255L, 31L, 214L, 7L, 226L, 95L, 124L, 198L, 186L, 48L, 68L, 157L, 86L, 149L, 162L, 19L, 171L, 247L, 177L, 143L, 62L, 237L, 153L, 188L, 183L, 107L, 74L, 11L, 231L, 132L, 130L, 192L, 245L, 61L, 12L, 110L, 38L, 147L, 235L, 35L, 51L, 16L, 89L, 27L, 54L, 138L, 98L, 71L, 156L, 240L, 206L, 77L, 135L, 176L, 137L, 119L, 181L, 9L, 133L, 173L, 217L, 20L, 154L, 14L, 146L, 243L, 102L, 99L, 167L, 208L, 202L, 197L, 250L, 164L, 101L, 105L, 41L, 56L, 120L, 169L, 141L, 216L, 220L, 219L, 241L, 78L, 72L, 57L, 40L, 104L, 165L, 251L, 25L, 203L, 184L, 248L, 75L, 189L, 64L, 69L, 195L, 96L, 17L, 238L, 80L, 93L, 23L, 45L), `(tostate)` = c(1, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 2, 2, 1, 2, 2, 2, 1, 2, 2, 2, 2, 1, 3, 2, 3, 2, 2, 3, 2, 2, 3, 2, 1, 2, 2, 2, 2, 3, 2, 1, 2, 1, 2, 2, 2, 2, 3, 1, 2, 2, 2, 1, 2, 2, 2, 3, 3, 2, 2, 2, 2, 3, 3, 2, 3, 2, 2, 2, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 3, 1, 2, 3, 3, 2, 2, 1, 2, 1, 2, 2, 3, 2, 2, 2, 2, 2, 2, 2, 2, 3, 2, 2, 2, 1, 1, 3, 2, 3, 3, 3, 3, 2, 3, 3, 2, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 2, 2, 2, 3, 3, 2, 2, 2, 2, 2, 2, 3, 2, 3, 2, 3, 2, 3, 3, 3, 3, 3, 3, 2, 3, 3, 2), `(timelag)` = c(0.167301606852561, 0.3010408510454, 0.326865123492345, 0.373379818629473, 0.444147979018943, 0.463039907882884, 0.503689229919938, 0.588790811598301, 0.645748993758942, 0.777970170602202, 0.993271194635708, 1.06335115169736, 1.19670573063659, 1.23358175813834, 1.60594620632657, 1.68466971058728, 1.69717255488757, 1.69891210470069, 1.70753057440278, 1.7716667172499, 1.78860554021411, 1.82958139332304, 1.83614749739054, 1.87757994240222, 1.8811577023007, 1.94473282188878, 1.99262343138036, 10.0195844521678, 10.394417598933, 10.496191308296, 10.8717317382293, 11.3763851798129, 11.7159918790512, 12.2000324354591, 14.5558520209811, 2.06416486447456, 2.15403129570777, 2.15757382069236, 2.16842943591225, 2.22858722279899, 2.26286172221628, 2.32244494219243, 2.40431244601521, 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mm.icov = NULL, subject.weights = NULL), qmodel = list(nstates = 3L, iso = 4, perm = c(1, 2, 3), qperm = 1:3, npars = 3, imatrix = c(0, 0, 0, 1, 0, 0, 1, 1, 0), qmatrix = c(-0.29402, 0, 0, 0.28163, -0.10204, 0, 0.01239, 0.10204, 0), inits = c(0.28163, 0.01239, 0.10204), constr = 1:3, ndpars = 3L, expm = 1), qcmodel = list( npars = 6, ndpars = 6, ncovs = 2, constr = c(1, 2, 3, 4, 5, 6), covlabels = c("strategy_nameNew 1", "strategy_nameNew 2" ), inits = c(0, 0, 0, 0, 0, 0), covmeans = c(`strategy_nameNew 1` = 0.352201257861635, `strategy_nameNew 2` = 0.314465408805031), cri = c(1, 0, 0, 1, 0, 0)), cmodel = list(ncens = 0, censor = NULL, states = NULL, states_list = NULL, index = NULL), hmodel = list(hidden = FALSE, models = c(0, 0, 0), nipars = 0, nicoveffs = 0, totpars = 0, ncoveffs = 0, ematrix = FALSE), paramdata = list(inits = c(qbase = -1.26716112628169, qbase = -4.39086558334109, qbase = -2.28239038570853, qcov = 0, qcov = 0), plabs = c("qbase", "qbase", "qbase", "qcov", "qcov", "qcov", "qcov", "qcov", "qcov"), allinits = c(qbase = -1.26716112628169, qbase = -4.39086558334109, qbase = -2.28239038570853, qcov = 0, qcov = 0, qcov = 0, qcov = 0, qcov = 0, qcov = 0), hmmpars = integer(0), fixed = FALSE, fixedpars = c(qcov = 5L, qcov = 6L, qcov = 8L, qcov = 9L), optpars = c(1L, 2L, 3L, 4L, 7L), auxpars = integer(0), constr = c(1, 2, 3, 4, 5, 6, 7, 8, 9), npars = 9, duppars = integer(0), nfix = 4L, nopt = 5L, ndup = 0L, ranges = c(0, 0, 0, -Inf, -Inf, -Inf, -Inf, -Inf, -Inf, Inf, Inf, Inf, Inf, Inf, Inf, Inf, Inf, Inf), params = c(qbase = -1.26716112628169, qbase = -4.39086558334109, qbase = -2.28239038570853, qcov = 0, qcov = 0, qcov = 0, qcov = 0, qcov = 0, qcov = 0)))
5: do.call("optim", optim.args)
6: msm.optim.optim(p = list(inits = c(qbase = -1.26716112628169, qbase = -4.39086558334109, qbase = -2.28239038570853, qcov = 0, qcov = 0), plabs = c("qbase", "qbase", "qbase", "qcov", "qcov", "qcov", "qcov", "qcov", "qcov"), allinits = c(qbase = -1.26716112628169, qbase = -4.39086558334109, qbase = -2.28239038570853, qcov = 0, qcov = 0, qcov = 0, qcov = 0, qcov = 0, qcov = 0), hmmpars = integer(0), fixed = FALSE, fixedpars = c(qcov = 5L, qcov = 6L, qcov = 8L, qcov = 9L), optpars = c(1L, 2L, 3L, 4L, 7L), auxpars = integer(0), constr = c(1, 2, 3, 4, 5, 6, 7, 8, 9), npars = 9, duppars = integer(0), nfix = 4L, nopt = 5L, ndup = 0L, ranges = c(0, 0, 0, -Inf, -Inf, -Inf, -Inf, -Inf, -Inf, Inf, Inf, Inf, Inf, Inf, Inf, Inf, Inf, Inf), params = c(qbase = -1.26716112628169, qbase = -4.39086558334109, qbase = -2.28239038570853, qcov = 0, qcov = 0, qcov = 0, qcov = 0, qcov = 0, qcov = 0)), gr = function (params, ...) { w <- list(...)$msmdata$subject.weights if (!is.null(w)) { deriv <- Ccall.msm(params, do.what = "deriv.subj", ...) apply(w * deriv, 2, sum) } else Ccall.msm(params, do.what = "deriv", ...)}, hessian = TRUE, msmdata = list(mf = list(strategy_name = c(3L, 3L, 3L, 1L, 1L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 3L, 3L, 3L, 1L, 1L, 3L, 3L, 3L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 2L, 2L, 2L, 3L, 3L, 3L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 3L, 3L, 2L, 2L, 2L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 3L, 3L, 1L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 1L, 1L, 1L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 2L, 2L, 2L), `(subject)` = c(1L, 1L, 1L, 127L, 127L, 209L, 209L, 250L, 250L, 267L, 267L, 267L, 280L, 280L, 285L, 285L, 285L, 378L, 378L, 378L, 440L, 440L, 440L, 478L, 478L, 488L, 488L, 500L, 500L, 507L, 507L, 507L, 528L, 528L, 528L, 569L, 569L, 569L, 612L, 612L, 612L, 677L, 677L, 678L, 678L, 678L, 787L, 787L, 787L, 827L, 827L, 829L, 829L, 829L, 860L, 860L, 860L, 890L, 890L, 905L, 905L, 905L, 950L, 950L, 966L, 966L, 1005L, 1005L, 1005L, 1010L, 1010L, 1010L, 1013L, 1013L, 1013L, 1016L, 1016L, 1016L, 1045L, 1045L, 1045L, 1151L, 1151L, 1151L, 1201L, 1201L, 1201L, 1204L, 1204L, 1204L, 1244L, 1244L, 1244L, 1263L, 1263L, 1263L, 1269L, 1269L, 1269L, 1270L, 1270L, 1270L, 1308L, 1308L, 1308L, 1315L, 1315L, 1315L, 1393L, 1393L, 1439L, 1439L, 1441L, 1441L, 1441L, 1447L, 1447L, 1486L, 1486L, 1486L, 1520L, 1520L, 1545L, 1545L, 1545L, 1572L, 1572L, 1572L, 1575L, 1575L, 1580L, 1580L, 1580L, 1619L, 1619L, 1633L, 1633L, 1633L, 1687L, 1687L, 1687L, 1695L, 1695L, 1695L, 1728L, 1728L, 1728L, 1742L, 1742L, 1752L, 1752L, 1761L, 1761L, 1761L, 1807L, 1807L, 1807L, 1847L, 1847L, 1847L, 1861L, 1861L, 1866L, 1866L, 1866L, 1869L, 1869L, 1877L, 1877L, 1906L, 1906L, 1911L, 1911L, 1911L, 1981L, 1981L, 1981L, 2025L, 2025L, 2028L, 2028L, 2073L, 2073L, 2073L, 2097L, 2097L, 2141L, 2141L, 2141L, 2143L, 2143L, 2143L, 2173L, 2173L, 2173L, 2187L, 2187L, 2187L, 2199L, 2199L, 2218L, 2218L, 2218L, 2223L, 2223L, 2223L, 2263L, 2263L, 2263L, 2312L, 2312L, 2314L, 2314L, 2314L, 2366L, 2366L, 2366L, 2371L, 2371L, 2371L, 2435L, 2435L, 2435L, 2446L, 2446L, 2446L, 2448L, 2448L, 2598L, 2598L, 2598L, 2619L, 2619L, 2801L, 2801L, 2816L, 2816L, 2816L, 2817L, 2817L, 2817L, 2823L, 2823L, 2836L, 2836L, 2864L, 2864L, 2864L, 2865L, 2865L, 2865L, 2870L, 2870L, 2879L, 2879L, 2879L), `(state)` = c(1, 2, 3, 1, 1, 1, 1, 1, 1, 1, 2, 3, 1, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 3, 1, 3, 1, 1, 1, 2, 3, 1, 2, 2, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 3, 1, 3, 1, 1, 1, 2, 3, 1, 2, 2, 1, 2, 3, 1, 2, 3, 1, 2, 2, 1, 2, 3, 1, 2, 2, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 2, 1, 2, 3, 1, 2, 2, 1, 2, 2, 1, 3, 1, 3, 1, 2, 2, 1, 1, 1, 2, 3, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 3, 1, 3, 1, 2, 2, 1, 2, 3, 1, 2, 2, 1, 2, 2, 1, 3, 1, 1, 1, 2, 3, 1, 2, 2, 1, 2, 2, 1, 3, 1, 2, 2, 1, 3, 1, 3, 1, 3, 1, 2, 2, 1, 2, 2, 1, 1, 1, 1, 1, 2, 3, 1, 3, 1, 2, 2, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 1, 1, 2, 2, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 2, 1, 2, 3, 1, 2, 2, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 2, 3, 1, 2, 3, 1, 3, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 3), `(time)` = c(0, 2.42022603865082, 14.6202584741099, 0, 1.06335115169736, 0, 3.37846853071824, 0, 5.91722974553704, 0, 4.58288009058403, 9.52924055461131, 0, 6.05977787502578, 0, 5.11314795230023, 14.1889426135388, 0, 3.9793853225728, 9.98404531133461, 0, 1.82958139332304, 11.7164812447244, 0, 8.25267813210891, 0, 5.28795059607339, 0, 2.40431244601521, 0, 3.27374095025703, 5.53660267247331, 0, 1.83614749739054, 6.8820353038609, 0, 2.32244494219243, 7.30246650986373, 0, 7.99197312290447, 15, 0, 0.373379818629473, 0, 9.97610073141581, 12.6211857463451, 0, 3.75908505063792, 6.51468300260603, 0, 5.07091985782608, 0, 1.69717255488757, 7.01308546587825, 0, 7.06069513880918, 15, 0, 1.8811577023007, 0, 4.90076951101563, 9.2030299551945, 0, 8.91516227995197, 0, 0.777970170602202, 0, 3.76012797928306, 12.7541593079442, 0, 5.4803828995153, 13.1962402455088, 0, 4.57313999656492, 13.0845508557175, 0, 5.63132673670023, 13.3382248074442, 0, 9.6100249037167, 10.6032960983524, 0, 1.60594620632657, 12.4776779445559, 0, 3.88422755035061, 5.87685098173097, 0, 5.19510834409654, 8.05593266150475, 0, 2.15403129570777, 11.8152541148148, 0, 3.43228499180158, 12.4636539884778, 0, 5.44870446876656, 12.0652837486224, 0, 6.88192152582238, 13.4552436723617, 0, 8.02066811347412, 15, 0, 4.50021161766982, 6.28881715788393, 0, 4.95045249025033, 0, 1.94473282188878, 0, 1.23358175813834, 3.81546577904373, 0, 2.45351897996223, 0, 5.75103343570654, 12.8507074011371, 0, 3.13150474335998, 0, 3.62361482018708, 15, 0, 1.70753057440278, 2.90423630503938, 0, 4.71622260985896, 0, 4.68820884543174, 10.6059529059576, 0, 5.67809275410179, 0, 5.74954350923768, 11.1949939368018, 0, 2.16842943591225, 9.5564392590454, 0, 4.11827209679337, 5.9958520391956, 0, 6.26891657464451, 11.293289180075, 0, 3.89833941377084, 0, 2.06416486447456, 0, 4.41538331020301, 10.4442594197434, 0, 5.51281272877163, 9.3304296140559, 0, 14.5558520209811, 15, 0, 3.96473119041544, 0, 6.82327246979789, 15, 0, 6.62903601714705, 0, 7.15516451563556, 0, 3.99949697666245, 0, 5.92132857335279, 8.07890239404514, 0, 5.72167968614231, 9.83430769527331, 0, 1.7716667172499, 0, 5.90151765849441, 0, 4.48052619859954, 12.8467609089349, 0, 3.71839352901634, 0, 4.42204647988183, 13.1059182373277, 0, 0.645748993758942, 5.43988305911687, 0, 2.22858722279899, 11.2371628721608, 0, 6.74261799564098, 10.4231144904582, 0, 0.588790811598301, 0, 6.71063269816809, 15, 0, 1.69891210470069, 7.27827564580366, 0, 6.63979810625763, 9.28839638130739, 0, 0.3010408510454, 0, 11.7159918790512, 15, 0, 7.42690194298182, 13.4159356094477, 0, 7.50595106923712, 15, 0, 10.496191308296, 10.8230564317884, 0, 0.503689229919938, 3.92409760504961, 0, 1.68466971058728, 0, 10.394417598933, 15, 0, 0.167301606852561, 0, 5.043442575261, 0, 4.30473713445075, 13.5908252629751, 0, 5.52245333077557, 13.1322277836806, 0, 6.52321177528359, 0, 4.89751752465963, 0, 4.06238924789648, 12.5009299948098, 0, 6.76183990406097, 15, 0, 0.463039907882884, 0, 3.19690445223537, 13.2164889044032 ), `(obstype)` = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), `(obstrue)` = c(1, 2, 3, 1, 1, 1, 1, 1, 1, 1, 2, 3, 1, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 3, 1, 3, 1, 1, 1, 2, 3, 1, 2, 2, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 3, 1, 3, 1, 1, 1, 2, 3, 1, 2, 2, 1, 2, 3, 1, 2, 3, 1, 2, 2, 1, 2, 3, 1, 2, 2, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 2, 1, 2, 3, 1, 2, 2, 1, 2, 2, 1, 3, 1, 3, 1, 2, 2, 1, 1, 1, 2, 3, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 3, 1, 3, 1, 2, 2, 1, 2, 3, 1, 2, 2, 1, 2, 2, 1, 3, 1, 1, 1, 2, 3, 1, 2, 2, 1, 2, 2, 1, 3, 1, 2, 2, 1, 3, 1, 3, 1, 3, 1, 2, 2, 1, 2, 2, 1, 1, 1, 1, 1, 2, 3, 1, 3, 1, 2, 2, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 1, 1, 2, 2, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 2, 1, 2, 3, 1, 2, 2, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 2, 3, 1, 2, 3, 1, 3, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 3), `(obs)` = 1:256, `(pcomb)` = c(NA, 1L, 2L, NA, 3L, NA, 4L, NA, 5L, NA, 6L, 7L, NA, 8L, NA, 9L, 10L, NA, 11L, 12L, NA, 13L, 14L, NA, 15L, NA, 16L, NA, 17L, NA, 18L, 19L, NA, 20L, 21L, NA, 22L, 23L, NA, 24L, 25L, NA, 26L, NA, 27L, 28L, NA, 29L, 30L, NA, 31L, NA, 32L, 33L, NA, 34L, 35L, NA, 36L, NA, 37L, 38L, NA, 39L, NA, 40L, NA, 41L, 42L, NA, 43L, 44L, NA, 45L, 46L, NA, 47L, 48L, NA, 49L, 50L, NA, 51L, 52L, NA, 53L, 54L, NA, 55L, 56L, NA, 57L, 58L, NA, 59L, 60L, NA, 61L, 62L, NA, 63L, 64L, NA, 65L, 66L, NA, 67L, 68L, NA, 69L, NA, 70L, NA, 71L, 72L, NA, 73L, NA, 74L, 75L, NA, 76L, NA, 77L, 78L, NA, 79L, 80L, NA, 81L, NA, 82L, 83L, NA, 84L, NA, 85L, 86L, NA, 87L, 88L, NA, 89L, 90L, NA, 91L, 92L, NA, 93L, NA, 94L, NA, 95L, 96L, NA, 97L, 98L, NA, 99L, 100L, NA, 101L, NA, 102L, 103L, NA, 104L, NA, 105L, NA, 106L, NA, 107L, 108L, NA, 109L, 110L, NA, 111L, NA, 112L, NA, 113L, 114L, NA, 115L, NA, 116L, 117L, NA, 118L, 119L, NA, 120L, 121L, NA, 122L, 123L, NA, 124L, NA, 125L, 126L, NA, 127L, 128L, NA, 129L, 130L, NA, 131L, NA, 132L, 133L, NA, 134L, 135L, NA, 136L, 137L, NA, 138L, 139L, NA, 140L, 141L, NA, 142L, NA, 143L, 144L, NA, 145L, NA, 146L, NA, 147L, 148L, NA, 149L, 150L, NA, 151L, NA, 152L, NA, 153L, 154L, NA, 155L, 156L, NA, 157L, NA, 158L, 159L)), mf.agg = list(strategy_name = c(2L, 3L, 1L, 1L, 3L, 3L, 1L, 2L, 1L, 2L, 3L, 1L, 3L, 2L, 3L, 3L, 2L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 1L, 3L, 1L, 2L, 3L, 1L, 3L, 2L, 2L, 3L, 3L, 1L, 1L, 1L, 3L, 1L, 2L, 1L, 2L, 3L, 3L, 2L, 3L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 1L, 2L, 2L, 2L, 3L, 1L, 3L, 2L, 1L, 1L, 3L, 2L, 3L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 3L, 3L, 1L, 3L, 2L, 3L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 1L, 2L, 2L, 3L, 2L, 2L, 2L, 2L, 3L, 1L, 1L, 2L, 3L, 1L, 3L, 1L, 2L, 1L, 2L, 2L, 1L, 3L, 2L, 2L, 3L, 2L, 3L, 1L, 2L, 2L, 1L, 2L, 3L, 3L, 3L, 1L, 1L, 1L, 3L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 3L, 3L, 2L, 1L, 2L, 2L, 1L, 1L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 2L, 3L, 1L, 3L, 3L), `(subject)` = c(2619L, 2312L, 2435L, 677L, 1847L, 2870L, 2446L, 2199L, 2143L, 966L, 1045L, 127L, 1572L, 1441L, 1151L, 2448L, 829L, 2223L, 1572L, 2025L, 1315L, 440L, 528L, 1695L, 890L, 1439L, 1201L, 2879L, 2598L, 2435L, 1151L, 1545L, 2314L, 1L, 1847L, 1752L, 1244L, 1911L, 1687L, 2173L, 507L, 569L, 500L, 1L, 1447L, 1441L, 678L, 2263L, 787L, 1204L, 1520L, 2879L, 507L, 2314L, 209L, 2446L, 1263L, 1545L, 2187L, 2097L, 787L, 1005L, 1807L, 1201L, 1742L, 1861L, 378L, 1906L, 2864L, 1981L, 1695L, 905L, 2816L, 1761L, 2141L, 2073L, 1315L, 1013L, 267L, 2598L, 1580L, 1575L, 2143L, 2836L, 905L, 267L, 1393L, 569L, 1728L, 2801L, 528L, 827L, 285L, 1204L, 488L, 829L, 1633L, 1269L, 1010L, 1807L, 2817L, 2223L, 1016L, 1619L, 1981L, 1633L, 1486L, 2028L, 250L, 1580L, 1911L, 2366L, 378L, 1761L, 280L, 1728L, 2823L, 1270L, 1269L, 1869L, 2263L, 2218L, 2187L, 2865L, 1866L, 1270L, 1308L, 612L, 860L, 1486L, 1877L, 1687L, 2366L, 2371L, 2371L, 2817L, 1016L, 1010L, 860L, 612L, 1308L, 1866L, 2865L, 478L, 2218L, 2073L, 2864L, 1013L, 2141L, 950L, 1005L, 2173L, 1263L, 285L, 2816L, 1045L, 1244L, 440L, 678L), `(fromstate)` = c(1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 2, 2, 1, 1, 2, 2, 1, 2, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 2, 2, 2, 2, 2, 1, 1, 1, 2, 1, 2, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 2, 1, 2, 2, 1, 2, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 2, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2, 1, 2, 1, 2, 1, 2, 2, 2, 2, 1, 1, 2, 2, 1, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 1, 2, 2, 1), `(time)` = c(0, 0, 10.496191308296, 0, 14.5558520209811, 0, 0, 0, 0, 0, 9.6100249037167, 0, 1.70753057440278, 0, 0, 0, 0, 0, 0, 0, 4.50021161766982, 0, 0, 4.11827209679337, 0, 0, 3.88422755035061, 3.19690445223537, 0, 0, 1.60594620632657, 3.62361482018708, 0, 2.42022603865082, 0, 0, 0, 5.92132857335279, 0, 0, 3.27374095025703, 0, 0, 0, 0, 1.23358175813834, 9.97610073141581, 6.63979810625763, 3.75908505063792, 5.19510834409654, 0, 0, 0, 11.7159918790512, 0, 0.503689229919938, 0, 0, 6.74261799564098, 0, 0, 0, 5.51281272877163, 0, 0, 0, 0, 0, 0, 5.72167968614231, 0, 4.90076951101563, 0, 0, 0, 0, 0, 0, 0, 10.394417598933, 0, 0, 0.645748993758942, 0, 0, 4.58288009058403, 0, 2.32244494219243, 6.26891657464451, 0, 1.83614749739054, 0, 0, 0, 0, 1.69717255488757, 5.74954350923768, 0, 0, 0, 0, 1.69891210470069, 0, 0, 0, 0, 0, 0, 0, 4.68820884543174, 0, 7.42690194298182, 3.9793853225728, 4.41538331020301, 0, 0, 0, 6.88192152582238, 5.44870446876656, 0, 0, 0, 0, 0, 0, 0, 8.02066811347412, 7.99197312290447, 0, 5.75103343570654, 0, 2.16842943591225, 0, 7.50595106923712, 0, 5.52245333077557, 5.63132673670023, 5.4803828995153, 7.06069513880918, 0, 0, 6.82327246979789, 6.76183990406097, 0, 6.71063269816809, 4.48052619859954, 4.06238924789648, 4.57313999656492, 4.42204647988183, 0, 3.76012797928306, 2.22858722279899, 3.43228499180158, 5.11314795230023, 4.30473713445075, 0, 2.15403129570777, 1.82958139332304, 0), `(obstype)` = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), `(obstrue)` = c(1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 2, 2, 1, 1, 2, 2, 1, 2, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 2, 2, 2, 2, 2, 1, 1, 1, 2, 1, 2, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 2, 1, 2, 2, 1, 2, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 2, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2, 1, 2, 1, 2, 1, 2, 2, 2, 2, 1, 1, 2, 2, 1, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 1, 2, 2, 1), `(obs)` = c(233L, 211L, 223L, 43L, 160L, 253L, 225L, 200L, 191L, 66L, 81L, 5L, 128L, 114L, 83L, 228L, 53L, 205L, 127L, 179L, 108L, 22L, 34L, 144L, 59L, 112L, 87L, 256L, 230L, 222L, 84L, 125L, 213L, 3L, 159L, 151L, 92L, 174L, 140L, 194L, 32L, 37L, 29L, 2L, 117L, 115L, 46L, 209L, 49L, 90L, 122L, 255L, 31L, 214L, 7L, 226L, 95L, 124L, 198L, 186L, 48L, 68L, 157L, 86L, 149L, 162L, 19L, 171L, 247L, 177L, 143L, 62L, 237L, 153L, 188L, 183L, 107L, 74L, 11L, 231L, 132L, 130L, 192L, 245L, 61L, 12L, 110L, 38L, 147L, 235L, 35L, 51L, 16L, 89L, 27L, 54L, 138L, 98L, 71L, 156L, 240L, 206L, 77L, 135L, 176L, 137L, 119L, 181L, 9L, 133L, 173L, 217L, 20L, 154L, 14L, 146L, 243L, 102L, 99L, 167L, 208L, 202L, 197L, 250L, 164L, 101L, 105L, 41L, 56L, 120L, 169L, 141L, 216L, 220L, 219L, 241L, 78L, 72L, 57L, 40L, 104L, 165L, 251L, 25L, 203L, 184L, 248L, 75L, 189L, 64L, 69L, 195L, 96L, 17L, 238L, 80L, 93L, 23L, 45L), `(tostate)` = c(1, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 2, 2, 1, 2, 2, 2, 1, 2, 2, 2, 2, 1, 3, 2, 3, 2, 2, 3, 2, 2, 3, 2, 1, 2, 2, 2, 2, 3, 2, 1, 2, 1, 2, 2, 2, 2, 3, 1, 2, 2, 2, 1, 2, 2, 2, 3, 3, 2, 2, 2, 2, 3, 3, 2, 3, 2, 2, 2, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 3, 1, 2, 3, 3, 2, 2, 1, 2, 1, 2, 2, 3, 2, 2, 2, 2, 2, 2, 2, 2, 3, 2, 2, 2, 1, 1, 3, 2, 3, 3, 3, 3, 2, 3, 3, 2, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 2, 2, 2, 3, 3, 2, 2, 2, 2, 2, 2, 3, 2, 3, 2, 3, 2, 3, 3, 3, 3, 3, 3, 2, 3, 3, 2), `(timelag)` = c(0.167301606852561, 0.3010408510454, 0.326865123492345, 0.373379818629473, 0.444147979018943, 0.463039907882884, 0.503689229919938, 0.588790811598301, 0.645748993758942, 0.777970170602202, 0.993271194635708, 1.06335115169736, 1.19670573063659, 1.23358175813834, 1.60594620632657, 1.68466971058728, 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1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), `(whicha)` = 1:159, `(noccsum)` = c(NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 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-0.314465408805031, 0.685534591194969, 0.685534591194969, -0.314465408805031, -0.314465408805031, -0.314465408805031, -0.314465408805031, -0.314465408805031, -0.314465408805031, 0.685534591194969, -0.314465408805031, -0.314465408805031, 0.685534591194969, -0.314465408805031, -0.314465408805031, 0.685534591194969, -0.314465408805031, 0.685534591194969, -0.314465408805031, 0.685534591194969, 0.685534591194969), mm.mcov = NULL, mm.hcov = NULL, mm.icov = NULL, subject.weights = NULL), qmodel = list(nstates = 3L, iso = 4, perm = c(1, 2, 3), qperm = 1:3, npars = 3, imatrix = c(0, 0, 0, 1, 0, 0, 1, 1, 0), qmatrix = c(-0.29402, 0, 0, 0.28163, -0.10204, 0, 0.01239, 0.10204, 0), inits = c(0.28163, 0.01239, 0.10204), constr = 1:3, ndpars = 3L, expm = 1), qcmodel = list( npars = 6, ndpars = 6, ncovs = 2, constr = c(1, 2, 3, 4, 5, 6), covlabels = c("strategy_nameNew 1", "strategy_nameNew 2" ), inits = c(0, 0, 0, 0, 0, 0), covmeans = c(`strategy_nameNew 1` = 0.352201257861635, `strategy_nameNew 2` = 0.314465408805031), cri = c(1, 0, 0, 1, 0, 0)), cmodel = list(ncens = 0, censor = NULL, states = NULL, states_list = NULL, index = NULL), hmodel = list(hidden = FALSE, models = c(0, 0, 0), nipars = 0, nicoveffs = 0, totpars = 0, ncoveffs = 0, ematrix = FALSE))
7: do.call(optfn, args)
8: msm.optim(opt.method, p, hessian, use.deriv, msmdata, qmodel, qcmodel, cmodel, hmodel, ...)
9: msm(state_id ~ time, subject = patient_id, data = onc3p[patient_id %in% sample(patient_id, 100)], covariates = list(`1-2` = ~strategy_name), qmatrix = qinit)
10: eval(code, test_env)
11: eval(code, test_env)
12: withCallingHandlers({ eval(code, test_env) if (!handled && !is.null(test)) { skip_empty() }}, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, message = handle_message, error = handle_error)
13: doTryCatch(return(expr), name, parentenv, handler)
14: tryCatchOne(expr, names, parentenv, handlers[[1L]])
15: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
16: doTryCatch(return(expr), name, parentenv, handler)
17: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]), names[nh], parentenv, handlers[[nh]])
18: tryCatchList(expr, classes, parentenv, handlers)
19: tryCatch(withCallingHandlers({ eval(code, test_env) if (!handled && !is.null(test)) { skip_empty() }}, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, message = handle_message, error = handle_error), error = handle_fatal, skip = function(e) { })
20: test_code(test = NULL, code = exprs, env = env, default_reporter = StopReporter$new())
21: source_file(path, env = env(env), desc = desc, error_call = error_call)
22: FUN(X[[i]], ...)
23: lapply(test_paths, test_one_file, env = env, desc = desc, error_call = error_call)
24: doTryCatch(return(expr), name, parentenv, handler)
25: tryCatchOne(expr, names, parentenv, handlers[[1L]])
26: tryCatchList(expr, classes, parentenv, handlers)
27: tryCatch(code, testthat_abort_reporter = function(cnd) { cat(conditionMessage(cnd), "\n") NULL})
28: with_reporter(reporters$multi, lapply(test_paths, test_one_file, env = env, desc = desc, error_call = error_call))
29: test_files_serial(test_dir = test_dir, test_package = test_package, test_paths = test_paths, load_helpers = load_helpers, reporter = reporter, env = env, stop_on_failure = stop_on_failure, stop_on_warning = stop_on_warning, desc = desc, load_package = load_package, error_call = error_call)
30: test_files(test_dir = path, test_paths = test_paths, test_package = package, reporter = reporter, load_helpers = load_helpers, env = env, stop_on_failure = stop_on_failure, stop_on_warning = stop_on_warning, load_package = load_package, parallel = parallel)
31: test_dir("testthat", package = package, reporter = reporter, ..., load_package = "installed")
32: test_check("hesim")
An irrecoverable exception occurred. R is aborting now ...
Flavor: r-devel-linux-x86_64-fedora-gcc