mssm: Multivariate State Space Models

Provides methods to perform parameter estimation and make analysis of multivariate observed outcomes through time which depends on a latent state variable. All methods scale well in the dimension of the observed outcomes at each time point. The package contains an implementation of a Laplace approximation, particle filters like suggested by Lin, Zhang, Cheng, & Chen (2005) <doi:10.1198/016214505000000349>, and the gradient and observed information matrix approximation suggested by Poyiadjis, Doucet, & Singh (2011) <doi:10.1093/biomet/asq062>.

Package details

AuthorBenjamin Christoffersen [cre, aut], Anthony Williams [cph]
MaintainerBenjamin Christoffersen <[email protected]>
Package repositoryView on CRAN
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mssm documentation built on June 1, 2019, 1:03 a.m.