Package: FKF.SP 0.3.3

Thomas Aspinall

FKF.SP: Fast Kalman Filtering Through Sequential Processing

Fast and flexible Kalman filtering and smoothing implementation utilizing sequential processing, designed for efficient parameter estimation through maximum likelihood estimation. Sequential processing is a univariate treatment of a multivariate series of observations and can benefit from computational efficiency over traditional Kalman filtering when independence is assumed in the variance of the disturbances of the measurement equation. Sequential processing is described in the textbook of Durbin and Koopman (2001, ISBN:978-0-19-964117-8). 'FKF.SP' was built upon the existing 'FKF' package and is, in general, a faster Kalman filter/smoother.

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]

FKF.SP_0.3.3.tar.gz
FKF.SP_0.3.3.tar.gz(r-4.5-noble)FKF.SP_0.3.3.tar.gz(r-4.4-noble)
FKF.SP_0.3.3.tgz(r-4.4-emscripten)FKF.SP_0.3.3.tgz(r-4.3-emscripten)
FKF.SP.pdf |FKF.SP.html
FKF.SP/json (API)
NEWS

# Install 'FKF.SP' in R:
install.packages('FKF.SP', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/tomaspinall/fkf.sp/issues

Uses libs:
  • openblas– Optimized BLAS

3.18 score 1 packages 3 scripts 709 downloads 1 mentions 2 exports 1 dependencies

Last updated 1 months agofrom:62d7dd5884. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 18 2024
R-4.5-linux-x86_64OKNov 18 2024

Exports:fkf.SPfks.SP

Dependencies:mathjaxr

Fast Kalman Filtering using Sequential Processing

Rendered fromFKFSP.Rmdusingknitr::rmarkdownon Nov 18 2024.

Last update: 2022-10-10
Started: 2020-12-18