ZIM (1.1.0)

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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 by Yang et al. (2013) and state-space models by Yang et al. (2015) . 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.

Maintainer: Ming Yang
Author(s): Ming Yang [aut, cre], Gideon Zamba [aut], Joseph Cavanaugh [aut]

License: GPL-3

Uses: MASS, pscl, TSA

Released over 1 year ago.

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