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 Jyväskylä Finland _______________________________________________ R-packages mailing list r-packa...@r-project.org https://stat.ethz.ch/mailman/listinfo/r-packages ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
