Package: ZIM
Title: Zero-Inflated Models (ZIM) for Count Time Series with Excess
        Zeros
Version: 1.1.0
Authors@R: c(
    person("Ming", "Yang", email = "mingyang@biostatstudio.com", role = c("aut", "cre")),
    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.
License: GPL-3
Encoding: UTF-8
RoxygenNote: 6.1.0
Imports: MASS
Suggests: pscl, TSA
URL: https://github.com/biostatstudio/ZIM
BugReports: https://github.com/biostatstudio/ZIM/issues
NeedsCompilation: no
Packaged: 2018-08-28 12:00:56 UTC; mingyang
Author: Ming Yang [aut, cre],
  Gideon Zamba [aut],
  Joseph Cavanaugh [aut]
Maintainer: Ming Yang <mingyang@biostatstudio.com>
Repository: CRAN
Date/Publication: 2018-08-28 13:04:25 UTC
Built: R 4.2.0; ; 2023-04-01 16:38:17 UTC; unix
