Package: sparsesurv
Title: Forecasting and Early Outbreak Detection for Sparse Count Data
Version: 0.1.1
Authors@R: c(
    person("Alexandros", "Angelakis",
           email = "alexandros.angelakis@swisstph.ch",
           role = c("aut", "cre")),
           person("Bryan","Nyawanda",role = "aut"),
           person("Penelope","Vounatsou",role = "aut")
           )
Description: Functions for fitting, forecasting, and early detection of outbreaks in
    sparse surveillance count time series. Supports negative binomial (NB),
    self-exciting NB, generalise autoregressive moving average (GARMA) NB , zero-inflated NB (ZINB), self-exciting ZINB, generalise autoregressive moving average ZINB, and hurdle formulations. Climatic and environmental covariates
    can be included in the regression component and/or the zero-modified components.
    Includes outbreak-detection algorithms for NB, ZINB, and hurdle models, with
    utilities for prediction and diagnostics.
License: GPL (>= 3)
Encoding: UTF-8
Depends: R (>= 4.1)
Imports: R2jags, coda, stats
Suggests: testthat (>= 3.0.0), knitr, rjags, rmarkdown, ggplot2,
        reshape2
Config/testthat/edition: 3
SystemRequirements: JAGS (>= 4.x)
URL: https://github.com/alexangelakis-ang/sparsesurv
BugReports: https://github.com/alexangelakis-ang/sparsesurv/issues
RoxygenNote: 7.3.2
NeedsCompilation: no
Packaged: 2025-09-04 08:36:20 UTC; angeal
Author: Alexandros Angelakis [aut, cre],
  Bryan Nyawanda [aut],
  Penelope Vounatsou [aut]
Maintainer: Alexandros Angelakis <alexandros.angelakis@swisstph.ch>
Repository: CRAN
Date/Publication: 2025-09-09 14:10:02 UTC
Built: R 4.6.0; ; 2026-04-26 04:55:31 UTC; unix
