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
Repository: https://mingstat.r-universe.dev
Date/Publication: 2026-06-02 23:29:07 UTC
RemoteUrl: https://github.com/mingstat/zim
RemoteRef: HEAD
RemoteSha: 889ea8805b001e625d2b429f51a9020b587610e9
NeedsCompilation: no
Packaged: 2026-07-02 09:49:47 UTC; root
Author: Ming Yang [aut, cre],
  Gideon Zamba [aut],
  Joseph Cavanaugh [aut]
Maintainer: Ming Yang <hustyangming@gmail.com>