rts2: Real-Time Disease Surveillance
Supports modelling real-time case data to facilitate the real-time
surveillance of infectious diseases and other point phenomena. The package provides automated computational grid generation over
an area of interest with methods to map covariates between geographies, model fitting including spatially aggregated case counts,
and predictions and visualisation. Both Bayesian and maximum likelihood methods are provided. Log-Gaussian Cox Processes are described by
Diggle et al. (2013) <doi:10.1214/13-STS441> and we provide both the low-rank approximation for Gaussian processes
described by Solin and Särkkä (2020) <doi:10.1007/s11222-019-09886-w> and Riutort-Mayol et al (2020) <doi:10.48550/arXiv.2004.11408> and the
nearest neighbour Gaussian process described by Datta et al (2016) <doi:10.1080/01621459.2015.1044091>. 'cmdstanr' can be downloaded at <https://mc-stan.org/cmdstanr/>.
| Version: |
0.7.4 |
| Depends: |
R (≥ 3.5.0), sf (≥ 1.0-14) |
| Imports: |
methods, R6, Rcpp (≥ 0.12.0), RcppParallel (≥ 5.0.1), rstan (≥ 2.26.0), rstantools (≥ 2.1.1), lubridate |
| LinkingTo: |
BH (≥ 1.66.0), Rcpp (≥ 0.12.0), RcppEigen (≥ 0.3.3.3.0), RcppParallel (≥ 5.0.1), rstan (≥ 2.26.0), StanHeaders (≥
2.32.0), glmmrBase (≥ 0.7.1), SparseChol (≥ 0.2.2) |
| Suggests: |
cmdstanr (≥ 0.4.0), testthat |
| Published: |
2024-04-03 |
| Author: |
Sam Watson  [aut,
cre] |
| Maintainer: |
Sam Watson <s.i.watson at bham.ac.uk> |
| License: |
CC BY-SA 4.0 |
| NeedsCompilation: |
yes |
| SystemRequirements: |
GNU make |
| CRAN checks: |
rts2 results |
Documentation:
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