Fast Kalman Filtering Through Sequential Processing

Fast and flexible Kalman filtering implementation utilizing sequential processing, designed for efficient parameter estimation through maximum likelihood estimation. 'FKF.SP' was built upon the existing 'FKF' package and was designed to generally increase the computational efficiency of Kalman filtering when independence is assumed in the measurement error of observations. Sequential processing is described in the textbook of Durbin and Koopman (2001, ISBN:978-0-19-964117-8).


News

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("FKF.SP")

0.1.0 by Thomas Aspinall, a month ago


https://github.com/TomAspinall/FKF.SP


Report a bug at https://github.com/TomAspinall/FKF.SP/issues


Browse source code at https://github.com/cran/FKF.SP


Authors: Thomas Aspinall [aut, cre] , Adrian Gepp [aut] , Geoff Harris [aut] , Simone Kelly [aut] , Colette Southam [aut] , Bruce Vanstone [aut] , David Luethi [ctb] , Philipp Erb [ctb] , Simon Otziger [ctb] , Paul Smith [ctb]


Documentation:   PDF Manual  


GPL-3 license


Imports mathjaxr, Rdpack, curl

Suggests knitr, rmarkdown, stats, FKF


Imported by NFCP.


See at CRAN