Package: ZIM
Title: Zero-Inflated Models for Count Time Series with Excess Zeros
Version: 1.1.2
Authors@R: c(
    person("Ming", "Yang", role = c("aut", "cre"), email = "hustyangming@gmail.com"),
    person("Gideon", "Zamba", role = "aut"),
    person("Joseph", "Cavanaugh", role = "aut")
    )
Description: Analyze count time series with excess zeros. 
    Two types of statistical models are supported: Markov regression by Yang et al.
    (2013) <doi:10.1016/j.stamet.2013.02.001> and state-space models by Yang et al. 
    (2015) <doi:10.1177/1471082X14535530>. They are also known as observation-driven and 
    parameter-driven models respectively in the time series literature. The functions used for 
    Markov regression or observation-driven models can also be used to fit ordinary regression models 
    with independent data under the zero-inflated Poisson (ZIP) or zero-inflated negative binomial (ZINB) 
    assumption. Besides, the package contains some miscellaneous functions to compute density, distribution, 
    quantile, and generate random numbers from ZIP and ZINB distributions.
URL: https://github.com/mingstat/ZIM, https://mingstat.github.io/ZIM/
BugReports: https://github.com/mingstat/ZIM/issues
License: GPL-3
Encoding: UTF-8
RoxygenNote: 7.3.3
Imports: MASS
Suggests: knitr, dplyr, pscl, TSA, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
LazyData: true
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2026-06-03 04:18:35 UTC; mingyang
Author: Ming Yang [aut, cre],
  Gideon Zamba [aut],
  Joseph Cavanaugh [aut]
Maintainer: Ming Yang <hustyangming@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-03 08:10:02 UTC
Built: R 4.5.2; ; 2026-06-03 11:53:23 UTC; unix
