Last updated on 2026-10-24 00:52:21 CEST.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 0.11.1 | 22.12 | 389.31 | 411.43 | OK | |
| r-devel-linux-x86_64-debian-gcc | 0.11.1 | 15.25 | 252.10 | 267.35 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 0.11.1 | 18.00 | 264.45 | 282.45 | OK | |
| r-devel-linux-x86_64-fedora-gcc | 0.11.1 | 16.00 | 261.87 | 277.87 | OK | |
| r-devel-windows-x86_64 | 0.11.1 | 27.00 | 437.00 | 464.00 | OK | |
| r-patched-linux-x86_64 | 0.11.1 | 19.33 | 371.39 | 390.72 | OK | |
| r-release-linux-x86_64 | 0.11.1 | 20.47 | 375.63 | 396.10 | OK | |
| r-release-macos-arm64 | 0.11.1 | 5.00 | 71.00 | 76.00 | OK | |
| r-release-macos-x86_64 | 0.11.1 | 16.00 | 252.00 | 268.00 | OK | |
| r-release-windows-x86_64 | 0.11.1 | 27.00 | 345.00 | 372.00 | OK | |
| r-oldrel-macos-arm64 | 0.11.1 | 4.00 | 72.00 | 76.00 | OK | |
| r-oldrel-macos-x86_64 | 0.11.1 | 16.00 | 218.00 | 234.00 | OK | |
| r-oldrel-windows-x86_64 | 0.11.1 | 31.00 | 515.00 | 546.00 | OK |
Version: 0.11.1
Check: tests
Result: ERROR
Running ‘testthat.R’ [88s/128s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> # This file is part of the standard setup for testthat.
> # It is recommended that you do not modify it.
> #
> # Where should you do additional test configuration?
> # Learn more about the roles of various files in:
> # * https://r-pkgs.org/testing-design.html#sec-tests-files-overview
> # * https://testthat.r-lib.org/articles/special-files.html
>
> library(testthat)
> library(OptSurvCutR)
== OptSurvCutR v0.11.1 ==
Docs: <https://github.com/paytonyau/OptSurvCutR>
Paper: Yau, Payton (2025) bioRxiv 10.1101/2025.10.08.681246
Cite: `citation('OptSurvCutR')`
>
> test_check("OptSurvCutR")
No valid results found with given parameters.
No valid results found with given parameters.
No valid results found with given parameters.
-- Optimal Cut-point Number Analysis (Systematic) ------------------------------
v Best Model: 1 Cut-points (Criterion: AIC)
i Optimal Thresholds: "59.927"
-- 3. Cox Proportional-Hazards --
Group HR Lower Upper P_Value Signif
groupG2 0.514 0.213 1.24 0.138
i Overall Model: Concordance = 0.574 | Log-rank p = 0.131
-- 4. Time-Dependent Diagnostics (Schoenfeld) --
-- 5. Analysis Parameters --
* Search Method: Systematic
* Predictor: predictor
* Criterion: AIC
* Maximum Cuts: 1
* Minimum Group Size (nmin): 5
-- Optimal Cut-point Number Analysis -------------------------------------------
Method: Systematic
Criterion: BIC
No optimal model could be determined.
-- Optimal Cut-point Number Analysis (Systematic) ------------------------------
Cannot summarise: no valid model was found.
-- Optimal Cut-point Number Analysis (Systematic) ------------------------------
v Best Model: 1 Cut-points (Criterion: BIC)
i Optimal Thresholds: "6.31"
-- 1. Model Comparison --
-- 2. Clinical Risk Cohorts --
-- 3. Cox Proportional-Hazards --
i Overall Model: Concordance = 0.755 | Log-rank p = 0
-- 4. Time-Dependent Diagnostics (Schoenfeld) --
-- 5. Analysis Parameters --
* Search Method: Systematic
* Predictor: predictor
* Criterion: BIC
* Maximum Cuts: 1
* Minimum Group Size (nmin): 5
Cannot generate plot: no valid IC values found.
i Finding optimal cut number: method = systematic
i Profiling IC surface for 1 cut-point(s)...
-- Optimal Cut-point Number Analysis (Systematic) ------------------------------
v Best Model: 0 Cut-points (Criterion: AIC)
-- 1. Model Comparison --
-- 3. Cox Proportional-Hazards --
i Overall Model: Concordance = 1 | Log-rank p = 0.061
-- 4. Time-Dependent Diagnostics (Schoenfeld) --
-- 5. Analysis Parameters --
* Search Method: Systematic
* Predictor: predictor
* Criterion: AIC
* Maximum Cuts: 1
* Minimum Group Size (nmin): 1
Saving _problems/test-plotting-75.R
Saving _problems/test-plotting-98.R
Saving _problems/test-plotting-137.R
Ignoring unknown labels:
* colour : "Strata"
i nmin 0.25 is a proportion. Min. group size set to 75.
i Running regularised systematic search for 1 cut-point(s)...
v Systematic grid optimisation complete.
i Using random seed 11 for reproducibility.
i Bootstrap `nmin` not set. Using 67 (90% of original) to improve stability.
i Validating 1 cut(s) from 'systematic' search using 'logrank' over regularised coordinate lattice.
i Running 30 replicates sequentially (n_cores = 1).
v 30 replicates completed.
i nmin 0.25 is a proportion. Min. group size set to 75.
i Running regularised systematic search for 1 cut-point(s)...
v Systematic grid optimisation complete.
i Using random seed 12 for reproducibility.
i Bootstrap `nmin` not set. Using 67 (90% of original) to improve stability.
i Validating 1 cut(s) from 'systematic' search using 'logrank' over regularised coordinate lattice.
i Running 40 replicates sequentially (n_cores = 1).
v 40 replicates completed.
Cut-point Stability Analysis (Bootstrap)
----------------------------------------
Original Optimal Cut-point(s): 50.746
Bootstrap Distribution Summary
-----------------------------
Cut Mean SD Median Q1 Q3
25% Cut1 49.954 1.368 50.17 49.844 50.477
95% Confidence Intervals
------------------------
Lower Upper
Cut 1 48.115 51.479
Validation Parameters
---------------------
Replicates Requested: 40
Successful Replicates: 40 / 40 ( 100 %)
Failed Replicates: 0
Cores Used: 1
Seed: 12
Minimum Group Size (nmin): 67
Method: systematic
Criterion: logrank
Covariates: None
Stability Assessment:
---------------------
Widest relative width (P10-P90): 4.4%
v Model Status: OPTIMAL (Tier 1)
Highly consistent (4.4%).
i nmin 0.25 is a proportion. Min. group size set to 75.
i Running regularised systematic search for 1 cut-point(s)...
v Systematic grid optimisation complete.
i Using random seed 14 for reproducibility.
i Bootstrap `nmin` not set. Using 67 (90% of original) to improve stability.
i Validating 1 cut(s) from 'systematic' search using 'logrank' over regularised coordinate lattice.
i Running 40 replicates sequentially (n_cores = 1).
v 40 replicates completed.
Cut-point Stability Analysis (Bootstrap)
----------------------------------------
Original Optimal Cut-point(s): 52.994
Bootstrap Distribution Summary
-----------------------------
Cut Mean SD Median Q1 Q3
25% Cut1 51.192 4.553 50.649 48.49 52.363
95% Confidence Intervals
------------------------
Lower Upper
Cut 1 47.57 66.848
Validation Parameters
---------------------
Replicates Requested: 40
Successful Replicates: 40 / 40 ( 100 %)
Failed Replicates: 0
Cores Used: 1
Seed: 14
Minimum Group Size (nmin): 67
Method: systematic
Criterion: logrank
Covariates: None
Stability Assessment:
---------------------
Widest relative width (P10-P90): 24.9%
v Model Status: OPTIMAL (Tier 1)
Highly consistent (24.9%).
i nmin 0.25 is a proportion. Min. group size set to 50.
i Running regularised systematic search for 1 cut-point(s)...
v Systematic grid optimisation complete.
i Using random seed 15 for reproducibility.
i Bootstrap `nmin` not set. Using 45 (90% of original) to improve stability.
i Validating 1 cut(s) from 'systematic' search using 'logrank' over regularised coordinate lattice.
i Running 30 replicates sequentially (n_cores = 1).
v 30 replicates completed.
Cut-point Stability Analysis (Bootstrap)
----------------------------------------
Original Optimal Cut-point(s): 53.716
Bootstrap Distribution Summary
-----------------------------
Cut Mean SD Median Q1 Q3
25% Cut1 49.726 8.698 50.17 49.167 53.241
95% Confidence Intervals
------------------------
Lower Upper
Cut 1 35.468 67.228
Validation Parameters
---------------------
Replicates Requested: 30
Successful Replicates: 30 / 30 ( 100 %)
Failed Replicates: 0
Cores Used: 1
Seed: 15
Minimum Group Size (nmin): 45
Method: systematic
Criterion: logrank
Covariates: None
Stability Assessment:
---------------------
i nmin 0.25 is a proportion. Min. group size set to 62.
i Running regularised systematic search for 1 cut-point(s)...
v Systematic grid optimisation complete.
i Using random seed 16 for reproducibility.
i Bootstrap `nmin` not set. Using 55 (90% of original) to improve stability.
i Validating 1 cut(s) from 'systematic' search using 'logrank' over regularised coordinate lattice.
i Running 30 replicates sequentially (n_cores = 1).
v 30 replicates completed.
Cut-point Stability Analysis (Bootstrap)
----------------------------------------
Original Optimal Cut-point(s): 49.908
Bootstrap Distribution Summary
-----------------------------
Cut Mean SD Median Q1 Q3
25% Cut1 49.67 5.225 48.636 47.717 49.935
95% Confidence Intervals
------------------------
Lower Upper
Cut 1 45.29 60.225
Validation Parameters
---------------------
Replicates Requested: 30
Successful Replicates: 30 / 30 ( 100 %)
Failed Replicates: 0
Cores Used: 1
Seed: 16
Minimum Group Size (nmin): 55
Method: systematic
Criterion: logrank
Covariates: None
Stability Assessment:
---------------------
Widest relative width (P10-P90): 19%
v Model Status: OPTIMAL (Tier 1)
Highly consistent (19%).
Widest relative width (P10-P90): 115.4%
x Model Status: UNSTABLE (Tier 4)
! Wide variation (115.4%).
x Report as an interval, or increase `nmin`.
Widest relative width (P10-P90): 115.4%
x Model Status: UNSTABLE (Tier 4)
! Wide variation (115.4%).
x Report as an interval, or increase `nmin`.
Cut-point Stability Analysis (Bootstrap)
----------------------------------------
Original Optimal Cut-point(s): 65.73
Successful Replicates: 20 / 20 ( 100 %)
Failed Replicates: 0
95% Confidence Intervals
------------------------
Lower Upper
Cut 1 35.336 67.058
Bootstrap Summary Statistics
---------------------------
Cut Mean SD Median Q1 Q3
25% Cut1 57.915 10.097 61.707 55.703 65.332
Hint: Use `summary()` or `plot()` to visualise stability.
Widest relative width (P10-P90): 115.4%
x Model Status: UNSTABLE (Tier 4)
! Wide variation (115.4%).
x Report as an interval, or increase `nmin`.
i Bootstrap `nmin` not set. Using 18 (90% of original) to improve stability.
i Validating 1 cut(s) from 'systematic' search using 'logrank' over regularised coordinate lattice.
i Running 25 replicates sequentially (n_cores = 1).
! 25 of 25 replicates failed.
i Bootstrap `nmin` not set. Using 18 (90% of original) to improve stability.
i Validating 1 cut(s) from 'systematic' search using 'logrank' over regularised coordinate lattice.
i Running 25 replicates sequentially (n_cores = 1).
! 25 of 25 replicates failed.
i nmin 0.2 is a proportion. Min. group size set to 60.
i Running regularised systematic search for 1 cut-point(s)...
v Systematic grid optimisation complete.
i Using random seed 3 for reproducibility.
i Bootstrap `nmin` not set. Using 54 (90% of original) to improve stability.
i Validating 1 cut(s) from 'systematic' search using 'logrank' over regularised coordinate lattice.
i Running 30 replicates sequentially (n_cores = 1).
v 30 replicates completed.
[ FAIL 3 | WARN 52 | SKIP 4 | PASS 143 ]
══ Skipped tests (4) ═══════════════════════════════════════════════════════════
• On CRAN (4): 'test-stability-metric.R:94:3', 'test-stability-metric.R:175:3',
'test-workflow-integration.R:50:3', 'test-workflow-integration.R:106:3'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test-plotting.R:75:3'): Schoenfeld residual canvas handles layout failures ──
Error in `plot_cutpoint_residuals(fixtures$res_base)`: Proportional hazards evaluation failed due to a singular model matrix.
Backtrace:
▆
1. └─OptSurvCutR::plot_cutpoint_residuals(fixtures$res_base) at test-plotting.R:75:3
2. └─cli::cli_abort("Proportional hazards evaluation failed due to a singular model matrix.")
3. └─rlang::abort(...)
── Error ('test-plotting.R:98:5'): S3 router executes all plot variant selections through proper generic class dispatch ──
Error in `plot_cutpoint_residuals(x, ...)`: Proportional hazards evaluation failed due to a singular model matrix.
Backtrace:
▆
1. ├─base::suppressMessages(...) at test-plotting.R:98:5
2. │ └─base::withCallingHandlers(...)
3. ├─base::suppressWarnings(plot(fixtures$res_base, type = layout_type))
4. │ └─base::withCallingHandlers(...)
5. ├─base::plot(fixtures$res_base, type = layout_type)
6. └─OptSurvCutR:::plot.find_cutpoint(fixtures$res_base, type = layout_type)
7. └─OptSurvCutR::plot_cutpoint_residuals(x, ...)
8. └─cli::cli_abort("Proportional hazards evaluation failed due to a singular model matrix.")
9. └─rlang::abort(...)
── Error ('test-plotting.R:137:7'): Exhaustive layout matrix testing for S3 plot routers across engine types ──
Error in `plot_cutpoint_residuals(x, ...)`: Proportional hazards evaluation failed due to a singular model matrix.
Backtrace:
▆
1. ├─base::suppressMessages(suppressWarnings(plot(obj, type = layout_type))) at test-plotting.R:137:7
2. │ └─base::withCallingHandlers(...)
3. ├─base::suppressWarnings(plot(obj, type = layout_type))
4. │ └─base::withCallingHandlers(...)
5. ├─base::plot(obj, type = layout_type)
6. └─OptSurvCutR:::plot.find_cutpoint(obj, type = layout_type)
7. └─OptSurvCutR::plot_cutpoint_residuals(x, ...)
8. └─cli::cli_abort("Proportional hazards evaluation failed due to a singular model matrix.")
9. └─rlang::abort(...)
[ FAIL 3 | WARN 52 | SKIP 4 | PASS 143 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 0.11.1
Check: re-building of vignette outputs
Result: ERROR
Error(s) in re-building vignettes:
...
--- re-building ‘bilirubin.Rmd’ using rmarkdown
Quitting from bilirubin.Rmd:335-337 [plot-diagnostic]
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
<error/rlang_error>
Error in `plot_cutpoint_residuals()`:
! Proportional hazards evaluation failed due to a singular model matrix.
---
Backtrace:
▆
1. ├─base::plot(cut_res, type = "diagnostic")
2. └─OptSurvCutR:::plot.find_cutpoint(cut_res, type = "diagnostic")
3. └─OptSurvCutR::plot_cutpoint_residuals(x, ...)
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Error: processing vignette 'bilirubin.Rmd' failed with diagnostics:
Proportional hazards evaluation failed due to a singular model matrix.
--- failed re-building ‘bilirubin.Rmd’
--- re-building ‘crc.Rmd’ using rmarkdown
Quitting from crc.Rmd:329-331 [plot-residuals]
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
<error/rlang_error>
Error in `plot_cutpoint_residuals()`:
! Proportional hazards evaluation failed due to a singular model matrix.
---
Backtrace:
▆
1. ├─base::plot(cutpoint_result, type = "diagnostic")
2. └─OptSurvCutR:::plot.find_cutpoint(cutpoint_result, type = "diagnostic")
3. └─OptSurvCutR::plot_cutpoint_residuals(x, ...)
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Error: processing vignette 'crc.Rmd' failed with diagnostics:
Proportional hazards evaluation failed due to a singular model matrix.
--- failed re-building ‘crc.Rmd’
SUMMARY: processing the following files failed:
‘bilirubin.Rmd’ ‘crc.Rmd’
Error: Vignette re-building failed.
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc