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.
Version: | 1.1.0 |
Imports: | MASS |
Suggests: | pscl, TSA |
Published: | 2018-08-28 |
Author: | Ming Yang [aut, cre], Gideon Zamba [aut], Joseph Cavanaugh [aut] |
Maintainer: | Ming Yang <mingyang at biostatstudio.com> |
BugReports: | https://github.com/biostatstudio/ZIM/issues |
License: | GPL-3 |
URL: | https://github.com/biostatstudio/ZIM |
NeedsCompilation: | no |
Materials: | README |
In views: | TimeSeries |
CRAN checks: | ZIM results |
Reference manual: | ZIM.pdf |
Package source: | ZIM_1.1.0.tar.gz |
Windows binaries: | r-devel: ZIM_1.1.0.zip, r-release: ZIM_1.1.0.zip, r-oldrel: ZIM_1.1.0.zip |
macOS binaries: | r-release: ZIM_1.1.0.tgz, r-oldrel: ZIM_1.1.0.tgz |
Old sources: | ZIM archive |
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