Package: KFAS
Version: 1.3.1
Date: 2018-01-05
Title: Kalman Filter and Smoother for Exponential Family State Space
        Models
Author: Jouni Helske <jouni.helske@iki.fi>
Maintainer: Jouni Helske <jouni.helske@iki.fi>
Depends: R (>= 3.1.0)
Imports: stats
Suggests: MASS, testthat, knitr, lme4
Description: State space modelling is an efficient and flexible method for 
    statistical inference of a broad class of time series and other data. KFAS 
    includes fast 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.
License: GPL (>= 2)
BugReports: https://github.com/helske/KFAS/issues
VignetteBuilder: knitr
RoxygenNote: 6.0.1
ByteCompile: true
NeedsCompilation: yes
Packaged: 2018-01-04 13:01:30 UTC; jouhe21
Repository: CRAN
Date/Publication: 2018-01-04 14:50:00 UTC
Built: R 3.3.3; x86_64-w64-mingw32; 2018-04-22 14:21:07 UTC; windows
Archs: i386, x64
