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ZIM
View on CRAN: Click
here
Download and install ZIM package within the R console
Install from CRAN:
install.packages("ZIM")
Install from Github:
library("remotes")
install_github("cran/ZIM") Install by package version:
library("remotes")
install_version("ZIM", "1.1.0") Attach the package and use:
library("ZIM")
Maintained by
Ming Yang
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2013-06-19
Latest Update: 2018-08-28
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.
How to cite:
Ming Yang (2013). ZIM: Zero-Inflated Models (ZIM) for Count Time Series with Excess Zeros. R package version 1.1.0, https://cran.r-project.org/web/packages/ZIM. Accessed 25 Jun. 2026.
Previous versions and publish date:
Other packages that cited ZIM R package
View ZIM citation profile
Other R packages that ZIM depends,
imports, suggests or enhances
Complete documentation for ZIM
Functions, R codes and Examples using
the ZIM R package
Some associated functions: ZIM-package . bshift . dpqr-zinb . dpqr-zip . dzim.control . dzim.filter . dzim.fit . dzim . dzim.plot . dzim.sim . dzim.smooth . injury . pvalue . syph . zim.control . zim.fit . zim .
Some associated R codes: dpqr.R . dzim.R . misc.R . package.R . zim.R . Full ZIM package functions and examples
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