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).


Reference manual

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0.1.0 by Thomas Aspinall, a month ago

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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