Package: coconots
Type: Package
Title: Convolution-Closed Models for Count Time Series
Version: 2.0.1
Date: 2025-07-24
Authors@R: c(
    person(given = "Manuel",
           family = "Huth",
           role = c("aut", "cre"),
           email = "manuel.huth@yahoo.com"),
    person(given = "Robert C.",
           family = "Jung",
           role = "aut"),
    person(given = "Andy",
           family = "Tremayne",
           role =  "aut"
           ))
Description: Useful tools for fitting, validating, and forecasting of practical convolution-closed time series models for low counts are provided. Marginal distributions of the data can be modelled via Poisson and Generalized Poisson innovations. Regression effects can be incorporated through time varying innovation rates. The models are described in Jung and Tremayne (2011) <doi:10.1111/j.1467-9892.2010.00697.x> and the model assessment tools are presented in Czado et al. (2009) <doi:10.1111/j.1541-0420.2009.01191.x> and, Tsay (1992) <doi:10.2307/2347612>.
LazyData: true
LinkingTo: Rcpp
RoxygenNote: 7.3.2
Depends: R (>= 4.0.2)
Imports: forecast, numDeriv, HMMpa, ggplot2, matrixStats,
        JuliaConnectoR, Rcpp, stats
Suggests: testthat (>= 3.0.0)
Config/testthat/edition: 3
License: MIT + file LICENSE
NeedsCompilation: yes
Packaged: 2025-07-24 11:25:35 UTC; manuel
Author: Manuel Huth [aut, cre],
  Robert C. Jung [aut],
  Andy Tremayne [aut]
Maintainer: Manuel Huth <manuel.huth@yahoo.com>
Repository: CRAN
Date/Publication: 2025-07-24 12:00:02 UTC
Built: R 4.5.1; x86_64-apple-darwin20; 2025-07-24 12:14:32 UTC; unix
Archs: coconots.so.dSYM
