# --------------------------------------------
# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
# --------------------------------------------
 
cff-version: 1.2.0
message: 'To cite package "sparsesurv" in publications use:'
type: software
license: GPL-3.0-or-later
title: 'sparsesurv: Forecasting and Early Outbreak Detection for Sparse Count Data'
version: 0.1.1
doi: 10.32614/CRAN.package.sparsesurv
abstract: 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.
authors:
- family-names: Angelakis
  given-names: Alexandros
  email: alexandros.angelakis@swisstph.ch
- family-names: Nyawanda
  given-names: Bryan
- family-names: Vounatsou
  given-names: Penelope
repository: https://alexangelakis-ang.r-universe.dev
repository-code: https://github.com/alexangelakis-ang/sparsesurv
commit: 3789f5930acc403c091cccfb33d34518309bd6eb
url: https://github.com/alexangelakis-ang/sparsesurv
date-released: '2025-09-04'
contact:
- family-names: Angelakis
  given-names: Alexandros
  email: alexandros.angelakis@swisstph.ch