Package: KFAS
Version: 1.3.7
Date: 2019-06-10
Title: Kalman Filter and Smoother for Exponential Family State Space
        Models
Authors@R: 
    person(given = "Jouni",
           family = "Helske",
           role = c("aut", "cre"),
           email = "jouni.helske@iki.fi",
           comment = c(ORCID = "0000-0001-7130-793X"))
Depends: R (>= 3.1.0)
Imports: stats
Suggests: knitr, lme4, MASS, Matrix, testthat
Description: 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.
License: GPL (>= 2)
BugReports: https://github.com/helske/KFAS/issues
VignetteBuilder: knitr
RoxygenNote: 6.1.1
Encoding: UTF-8
ByteCompile: true
NeedsCompilation: yes
Packaged: 2019-06-10 07:06:40 UTC; jouhe21
Author: Jouni Helske [aut, cre] (<https://orcid.org/0000-0001-7130-793X>)
Maintainer: Jouni Helske <jouni.helske@iki.fi>
Repository: CRAN
Date/Publication: 2019-06-10 08:50:03 UTC
Built: R 3.6.3; x86_64-w64-mingw32; 2020-08-05 01:14:26 UTC; windows
Archs: i386, x64
