Zero-Inflated Models for Count Time Series with Excess Zeros
Fits observation-driven and parameter-driven models for count time series with excess zeros. package
The package ZIM contains functions to fit statistical models for count time series with excess zeros (Yang et al., 2013, 2015). The main function for fitting observation-driven models is zim, and the main function for fitting parameter-driven models is dzim.
The observation-driven models for zero-inflated count time series can also be fit using the function zeroinfl from the pscl package (Zeileis et al., 2008). Fitting parameter-driven models is based on sequential Monte Carlo (SMC) methods, which are computer intensive and could take several hours to estimate the model parameters.
Yang, M., Cavanaugh, J. E., and Zamba, G. K. D. (2015). State-space models for count time series with excess zeros. Statistical Modelling, 15 :70-90
Yang, M., Zamba, G. K. D., and Cavanaugh, J. E. (2013). Markov regression models for count time series with excess zeros: A partial likelihood approach. Statistical Methodology, 14 :26-38.
Zeileis, A., Kleiber, C., and Jackman, S. (2008). Regression models for count data in R. Journal of Statistical Software, 27 (8).