Jouni Lehtonen
2009-Aug-19 10:45 UTC
[R] [R-pkgs] New package for multivariate Kalman filtering, smoothing, simulation and forecasting
Dear all, I am pleased to announce the CRAN release of a new package called 'KFAS' - Kalman filter and smoother. The package KFAS contains functions of multivariate Kalman filter, smoother, simulation smoother and forecasting. It uses univariate approach algorithm (aka sequential processing), which is faster than normal method, and it also allows mean square prediction error matrix Ft to be singular. Filtering, smoothing and simulation functions are all written in Fortran. Functions allow time-variant system matrices and missing observations. In case distributions of some or all elements of initial state vector are unknown, functions use exact diffuse initialisation. I hope that this package will be useful for people working with state space models and time series in general. Any feedback is appreciated. Yours, Jouni Lehtonen University of Jyv?skyl? Finland _______________________________________________ R-packages mailing list R-packages at r-project.org https://stat.ethz.ch/mailman/listinfo/r-packages
Hi, I tried to manage exponential family state-space model with the packages KFAS. The problem is that my data set includes some NA observation and it seems not working. Any suggestion? Thanks in advance, Federico -- View this message in context: http://r.789695.n4.nabble.com/R-pkgs-New-package-for-multivariate-Kalman-filtering-smoothing-simulation-and-forecasting-tp903589p3027907.html Sent from the R help mailing list archive at Nabble.com.