Package: rts2
Title: Real-Time Disease Surveillance
Version: 0.5
Authors@R: 
    person(given = "Sam",
           family = "Watson",
           role = c("aut", "cre"),
           email = "s.i.watson@bham.ac.uk",
           comment = c(ORCID = "0000-0002-8972-769X"))
Description: 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>.
License: CC BY-SA 4.0
Encoding: UTF-8
RoxygenNote: 7.2.3
Biarch: true
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
Suggests: cmdstanr (>= 0.4.0), testthat
LinkingTo: BH (>= 1.66.0), Rcpp (>= 0.12.0), RcppEigen (>= 0.3.3.3.0),
        RcppParallel (>= 5.0.1), rstan (>= 2.18.1), StanHeaders (>=
        2.18.0)
SystemRequirements: GNU make
URL: http://www.sam-watson.xyz/vignette.html
Additional_repositories: https://mc-stan.org/r-packages/
NeedsCompilation: yes
Packaged: 2023-04-18 11:06:08 UTC; samue
Author: Sam Watson [aut, cre] (<https://orcid.org/0000-0002-8972-769X>)
Maintainer: Sam Watson <s.i.watson@bham.ac.uk>
Repository: CRAN
Date/Publication: 2023-04-18 11:40:02 UTC
Built: R 4.3.0; x86_64-apple-darwin20; 2023-04-22 01:28:10 UTC; unix
Archs: rts2.so.dSYM
