KFAS: Exponential Family State Space Models in R

Abstract

State space modelling is an efficient and flexible method for statistical inference of a broad class of time series and other data. This paper describes an R package KFAS for state space modelling with the observations from an exponential family, namely Gaussian, Poisson, binomial, negative binomial and gamma distributions. After introducing the basic theory behind Gaussian and non-Gaussian state space models, an illustrative example of Poisson time series forecasting is provided. Finally, a comparison to alternative R packages suitable for non-Gaussian time series modelling is presented.

39 pages, 7 figures. This is a preprint version of an article to appear in the Journal of Statistical Software. Change to previous version: Added grant number to acknowledgments

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