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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.
Version: | 0.1.1 |
Depends: | R (≥ 4.1) |
Imports: | R2jags, coda, stats |
Suggests: | testthat (≥ 3.0.0), knitr, rjags, rmarkdown, ggplot2, reshape2 |
Published: | 2025-09-09 |
DOI: | 10.32614/CRAN.package.sparsesurv |
Author: | Alexandros Angelakis [aut, cre], Bryan Nyawanda [aut], Penelope Vounatsou [aut] |
Maintainer: | Alexandros Angelakis <alexandros.angelakis at swisstph.ch> |
BugReports: | https://github.com/alexangelakis-ang/sparsesurv/issues |
License: | GPL (≥ 3) |
URL: | https://github.com/alexangelakis-ang/sparsesurv |
NeedsCompilation: | no |
SystemRequirements: | JAGS (>= 4.x) |
Materials: | README, NEWS |
CRAN checks: | sparsesurv results |
Reference manual: | sparsesurv.html , sparsesurv.pdf |
Package source: | sparsesurv_0.1.1.tar.gz |
Windows binaries: | r-devel: not available, r-release: not available, r-oldrel: sparsesurv_0.1.1.zip |
macOS binaries: | r-release (arm64): sparsesurv_0.1.1.tgz, r-oldrel (arm64): sparsesurv_0.1.1.tgz, r-release (x86_64): sparsesurv_0.1.1.tgz, r-oldrel (x86_64): sparsesurv_0.1.1.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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