rts2: Real-Time Disease Surveillance

Supports modelling real-time case data to facilitate the real-time surveillance of infectious disease. A simple grid class structure is provided to generate a computational grid over an area of interest with methods to map covariates between geographies. An approximate log-Gaussian Cox Process model is fit using 'rstan' or 'cmdstanr' and provides output and analysis as 'sf' objects for simple visualisation. 'cmdstanr' can be downloaded at <https://mc-stan.org/cmdstanr/>. 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) <arXiv:2004.11408> and the nearest neighbour Gaussian process described by Datta et al (2016) <doi:10.1080/01621459.2015.1044091>.

Version: 0.4
Depends: R (≥ 3.4.0)
Imports: methods, R6, Rcpp (≥ 0.12.0), RcppParallel (≥ 5.0.1), rstan (≥ 2.18.1), rstantools (≥ 2.1.1), sf (≥ 1.0-5), lubridate
LinkingTo: BH (≥ 1.66.0), Rcpp (≥ 0.12.0), RcppEigen (≥, RcppParallel (≥ 5.0.1), rstan (≥ 2.18.1), StanHeaders (≥ 2.18.0)
Suggests: cmdstanr (≥ 0.4.0), testthat
Published: 2022-10-27
Author: Sam Watson ORCID iD [aut, cre]
Maintainer: Sam Watson <s.i.watson at bham.ac.uk>
License: CC BY-SA 4.0
URL: http://www.sam-watson.xyz/vignette.html
NeedsCompilation: yes
SystemRequirements: GNU make
CRAN checks: rts2 results


Reference manual: rts2.pdf


Package source: rts2_0.4.tar.gz
Windows binaries: r-devel: rts2_0.4.zip, r-release: rts2_0.4.zip, r-oldrel: rts2_0.4.zip
macOS binaries: r-release (arm64): rts2_0.4.tgz, r-oldrel (arm64): rts2_0.4.tgz, r-release (x86_64): rts2_0.4.tgz, r-oldrel (x86_64): rts2_0.4.tgz
Old sources: rts2 archive


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