KFAS: Exponential Family State Space Models in R
Helske, J. (2017). KFAS: Exponential Family State Space Models in R. Journal of Statistical Software, 78(10). https://doi.org/10.18637/jss.v078.i10
Published inJournal of Statistical Software
© Helske, 2017. This is an open access article distributed under the terms of a Creative Commons License.
State space modeling is an efficient and flexible method for statistical inference of a broad class of time series and other data. This paper describes the R package KFAS for state space modeling 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 modeling is presented.
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Except where otherwise noted, this item's license is described as © Helske, 2017. This is an open access article distributed under the terms of a Creative Commons License.
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