Journal of Statistical Software

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Sample volume 1
Title State Space Models in R
Author Petris Giovanni, Petrone Sonia
Abstract
We give an overview of some of the software tools available in R, either as builtin
functions or contributed packages, for the analysis of state space models. Several
illustrative examples are included, covering constant and time-varying models for both
univariate and multivariate time series. Maximum likelihood and Bayesian methods to
obtain parameter estimates are considered.
Citation
Keywords Kalman lter, state space models, unobserved components, software tools, R.
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