r-zim 1.1.0 Zero-inflated models (ZIM) for count time series with excess zeros
Analyze count time series with excess zeros. Two types of statistical models are supported: Markov regression and state-space models. 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. The package also contains miscellaneous functions to compute density, distribution, quantile, and generate random numbers from ZIP and ZINB distributions.