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State space modelling is an efficient and flexible framework for statistical inference of a broad class of time series and other data. KFAS includes computationally efficient functions for Kalman filtering, smoothing, forecasting, and simulation of multivariate exponential family state space models, with observations from Gaussian, Poisson, binomial, negative binomial, and gamma distributions. See the paper by Helske (2017) <doi:10.18637/jss.v078.i10> for details.
Package details 


Author  Jouni Helske [aut, cre] (<https://orcid.org/000000017130793X>) 
Maintainer  Jouni Helske <jouni.helske@iki.fi> 
License  GPL (>= 2) 
Version  1.3.7 
Package repository  View on CRAN 
Installation 
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