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mssm
View on CRAN: Click
here
Download and install mssm package within the R console
Install from CRAN:
install.packages("mssm")
Install from Github:
library("remotes")
install_github("cran/mssm") Install by package version:
library("remotes")
install_version("mssm", "0.1.6") Attach the package and use:
library("mssm")
Maintained by
Benjamin Christoffersen
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-05-24
Latest Update:
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)
.
How to cite:
Benjamin Christoffersen (2019). mssm: Multivariate State Space Models. R package version 0.1.6, https://cran.r-project.org/web/packages/mssm. Accessed 18 Sep. 2026.
Previous versions and publish date:
Other packages that cited mssm R package
View mssm citation profile
Other R packages that mssm depends,
imports, suggests or enhances
Functions, R codes and Examples using
the mssm R package
Some associated functions: get_ess . logLik.mssm . mssm-Laplace . mssm-package . mssm-pf . mssm-smoother . mssm . mssm_control . plot.mssm . plot.mssmEss .
Some associated R codes: RcppExports.R . catch-routine-registration.R . ess.R . mssm.R . plot.R . print.R . roxygen-tags.R . Full mssm package functions and examples
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