Package: mssm
Type: Package
Title: Multivariate State Space Models
Version: 0.1.6
Authors@R: c(
  person("Benjamin", "Christoffersen", 
         email = "boennecd@gmail.com", 
         role = c("cre", "aut"), 
         comment = c(ORCID = "0000-0002-7182-1346")), 
  person("Anthony", "Williams", 
         role = c("cph")))
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)
  <doi:10.1198/016214505000000349>, and the gradient and observed information
  matrix approximation suggested by Poyiadjis, Doucet, & Singh (2011) 
  <doi:10.1093/biomet/asq062>.
BugReports: https://github.com/boennecd/mssm/issues
URL: https://github.com/boennecd/mssm
License: GPL-2
Encoding: UTF-8
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, Ecdat
NeedsCompilation: yes
Packaged: 2022-01-28 14:34:24 UTC; boennecd
Author: Benjamin Christoffersen [cre, aut]
    (<https://orcid.org/0000-0002-7182-1346>),
  Anthony Williams [cph]
Maintainer: Benjamin Christoffersen <boennecd@gmail.com>
Repository: CRAN
Date/Publication: 2022-01-31 07:40:10 UTC
Built: R 4.1.2; x86_64-apple-darwin17.0; 2022-02-01 12:59:16 UTC; unix
Archs: mssm.so.dSYM
