Package: walker
Type: Package
Title: Efficient Bayesian Linear Regression with Time-Varying
        Coefficients
Version: 0.1.0
Date: 2017-06-15
Author: Jouni Helske
Maintainer: Jouni Helske <jouni.helske@iki.fi>
Description: Fully Bayesian linear regression where the regression 
    coefficients are allowed to vary over "time", either as independent random 
    walks. All computations are done using Hamiltonian Monte Carlo provided by 
    Stan, using a state space representation of the model in order to marginalise 
    over the coefficients for efficient sampling.
License: GPL (>= 2)
Suggests: knitr (>= 1.11), rmarkdown (>= 0.8.1), testthat
Depends: R (>= 3.0.2), rstan (>= 2.14.1)
Imports: Rcpp (>= 0.12.9), methods
LinkingTo: StanHeaders (>= 2.14.0.1), rstan (>= 2.14.1), BH (>=
        1.62.0.1), Rcpp (>= 0.12.9), RcppEigen (>= 0.3.2.9.0)
VignetteBuilder: knitr
SystemRequirements: C++11
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2017-06-15 14:11:29 UTC; jouni
Repository: CRAN
Date/Publication: 2017-06-15 15:18:48 UTC
