Bayesian and Likelihood Analysis of Dynamic Linear Models

Provides routines for Maximum likelihood, Kalman filtering and smoothing, and Bayesian analysis of Normal linear State Space models, also known as Dynamic Linear Models.


1. Put any C/C++/Fortran code in 'src'
2. If you have compiled code, add a .First.lib() function in 'R'
   to load the shared library
3. Edit the help file skeletons in 'man'
4. Run R CMD build to create the index files
5. Run R CMD check to check the package
6. Run R CMD build to make the package file


Read "Writing R Extensions" for more information.

Reference manual

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install.packages("dlm")

1.1-6.1 by Giovanni Petris, 2 years ago


Browse source code at https://github.com/cran/dlm


Authors: Giovanni Petris [aut, cre] , Wally Gilks [ctb] (Author of original C code for ARMS)


Documentation:   PDF Manual  


GPL (>= 2) license


Imports stats, utils, methods, grDevices, graphics

Suggests MASS


Imported by CureDepCens, DepCens, ExGaussEstim, MfUSampler, NTS, RGAP, dlmwwbe, fasster, trendseries.

Depended on by longitudinalANAL.

Suggested by ZeBook, dfms, maxLik.


See at CRAN