Zero-Inflated Models for Count Time Series with Excess Zeros R package ZIM version 1.1.2 CRAN Task View: TimeSeries (https://CRAN.R-project.org/view=TimeSeries) 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. Software Imports: MASS Suggests: knitr, dplyr, pscl, TSA, rmarkdown, testthat (>= 3.0.0) Ming Yang <hustyangming@gmail.com> Comprehensive R Archive Network (CRAN) Ming Yang [aut, cre], Gideon Zamba [aut], Joseph Cavanaugh [aut] GPL-3 2026-06-03 application/tgz https://CRAN.R-project.org/package=ZIM doi:10.32614/CRAN.package.ZIM