walker: Efficient Bayesian Linear Regression with Time-Varying Coefficients

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.

Version: 0.1.0
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)
Suggests: knitr (≥ 1.11), rmarkdown (≥ 0.8.1), testthat
Published: 2017-06-15
Author: Jouni Helske
Maintainer: Jouni Helske <jouni.helske at iki.fi>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
SystemRequirements: C++11
CRAN checks: walker results

Downloads:

Reference manual: walker.pdf
Vignettes: Efficient Bayesian linear regression with time-varying coefficients
Package source: walker_0.1.0.tar.gz
Windows binaries: r-devel: walker_0.1.0.zip, r-release: walker_0.1.0.zip, r-oldrel: walker_0.1.0.zip
OS X El Capitan binaries: r-release: walker_0.1.0.tgz
OS X Mavericks binaries: r-oldrel: walker_0.1.0.tgz

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