DESCRIPTION

Package: surveil
Title: Time Series Models for Disease Surveillance 
Version: 0.3.0
Date: 2024-07-07
Authors@R: 
    person(given = "Connor",
           family = "Donegan",
           role = c("aut", "cre"),
           email = "connor.donegan@gmail.com",
           comment = c(ORCID = "0000-0002-9698-5443"))
URL: https://connordonegan.github.io/surveil/, https://github.com/ConnorDonegan/surveil/
Description: Fits time trend models for routine disease surveillance tasks and returns probability distributions for a variety of quantities of interest, including age-standardized rates, period and cumulative percent change, and measures of health inequality. The models are appropriate for count data such as disease incidence and mortality data, employing a Poisson or binomial likelihood and the first-difference (random-walk) prior for unknown risk. Optionally add a covariance matrix for multiple, correlated time series models. Inference is completed using Markov chain Monte Carlo via the Stan modeling language. References: Donegan, Hughes, and Lee (2022) <doi:10.2196/34589>; Stan Development Team (2021) <https://mc-stan.org>; Theil (1972, ISBN:0-444-10378-3).
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.1
Biarch: true
Depends: 
    R (>= 3.5.0)
Imports:
    rstantools (>= 2.1.1),
    methods,
    Rcpp (>= 0.12.0),
    RcppParallel (>= 5.0.1),
    rstan (>= 2.26.0),
    tidybayes (>= 3.0.0),
    dplyr (>= 1.0.7),
    rlang (>= 0.4.0),
    tidyr (>= 1.1.0),
    ggplot2 (>= 3.0.0),
    gridExtra (>= 2.0),
    scales (>= 0.4.0),
    ggdist (>= 3.0.0)
LinkingTo: 
    BH (>= 1.66.0),
    Rcpp (>= 0.12.0),
    RcppEigen (>= 0.3.3.3.0),
    RcppParallel (>= 5.0.1),
    rstan (>= 2.26.0),
    StanHeaders (>= 2.26.0)
Suggests:
    rmarkdown,
    knitr,
    testthat
SystemRequirements: GNU make
VignetteBuilder: knitr