Package: KFAS 1.5.1
Jouni Helske
KFAS: Kalman Filter and Smoother for Exponential Family State Space Models
State space modelling is an efficient and flexible framework for statistical inference of a broad class of time series and other data. KFAS includes computationally efficient functions for Kalman filtering, smoothing, forecasting, and simulation of multivariate exponential family state space models, with observations from Gaussian, Poisson, binomial, negative binomial, and gamma distributions. See the paper by Helske (2017) <doi:10.18637/jss.v078.i10> for details.
Authors:
KFAS_1.5.1.tar.gz
KFAS_1.5.1.tar.gz(r-4.5-noble)KFAS_1.5.1.tar.gz(r-4.4-noble)
KFAS_1.5.1.tgz(r-4.4-emscripten)KFAS_1.5.1.tgz(r-4.3-emscripten)
KFAS.pdf |KFAS.html✨
KFAS/json (API)
| # Install 'KFAS' in R: |
| install.packages('KFAS', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/helske/kfas/issues
- GlobalTemp - Two series of average global temperature deviations for years 1880-1987
- alcohol - Alcohol related deaths in Finland 1969-2013
- boat - Oxford-Cambridge boat race results 1829-2011
- sexratio - Number of males and females born in Finland from 1751 to 2011
Last updated 1 years agofrom:2cb53bad0a. Checks:OK: 2. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 18 2024 |
| R-4.5-linux-x86_64 | OK | Dec 18 2024 |
Exports:approxSSMartransformfitSSMimportanceSSMis.SSModelKFSldlmvInnovationsrename_statessignalsimulateSSMSSMarimaSSMcustomSSMcycleSSModelSSMregressionSSMseasonalSSMtrendsubset<-transformSSM
Dependencies:
