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mssm  

Multivariate State Space Models
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]
All associated links for this package
First Published: 2019-05-24
Latest Update: 2024-01-12
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
Previous versions and publish date:
0.1.0 (2019-05-24 14:30), 0.1.1 (2019-06-01 00:02), 0.1.2 (2019-08-09 00:50), 0.1.3 (2019-11-07 01:20), 0.1.4 (2020-12-15 23:30), 0.1.5 (2021-10-05 09:10), 0.1.6 (2022-01-31 08:40)
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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