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>.

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Description file content

Package
mssm
Type
Package
Title
Multivariate State Space Models
Version
0.1.3
Description
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) , and the gradient and observed information matrix approximation suggested by Poyiadjis, Doucet, & Singh (2011) .
License
GPL-2
Encoding
UTF-8
LazyData
true
Depends
R (>= 3.5.0), stats, graphics
LinkingTo
Rcpp, RcppArmadillo, testthat, nloptr (>= 1.2.0)
Imports
Rcpp, nloptr (>= 1.2.0)
RoxygenNote
6.1.1
SystemRequirements
C++11
Suggests
testthat, microbenchmark, Ecdat
NeedsCompilation
yes
Packaged
2019-11-06 13:08:03 UTC; boennecd
Author
Benjamin Christoffersen [cre, aut], Anthony Williams [cph]
Maintainer
Benjamin Christoffersen
Repository
CRAN
Date/Publication
2019-11-07 00:20:02 UTC

install.packages('mssm')

0.1.3

7 days ago

Benjamin Christoffersen

GPL-2

Depends on

R (>= 3.5.0), stats, graphics

Imports

Rcpp, nloptr (>= 1.2.0)

Suggests

testthat, microbenchmark, Ecdat

Discussions