walker

Bayesian Regression with Time-Varying Coefficients

Bayesian dynamic regression models where the regression coefficients can vary over time as random walks. Gaussian, Poisson, and binomial observations are supported. The Markov chain Monte Carlo 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.

Total

674

Last month

168

Last week

47

Average per day

6

Daily downloads

Total downloads

Description file content

Package
walker
Type
Package
Title
Bayesian Regression with Time-Varying Coefficients
Version
0.2.0
Date
2017-07-11
Author
Jouni Helske
Maintainer
Jouni Helske
Description
Bayesian dynamic regression models where the regression coefficients can vary over time as random walks. Gaussian, Poisson, and binomial observations are supported. The Markov chain Monte Carlo 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
diagis, gridExtra, knitr (>= 1.11), rmarkdown (>= 0.8.1), testthat
Depends
R (>= 3.0.2), Rcpp (>= 0.12.9), bayesplot, rstan (>= 2.16.2)
Imports
dplyr, ggplot2, KFAS, methods
LinkingTo
StanHeaders (>= 2.16.0), rstan (>= 2.16.2), BH (>= 1.62.0.1), Rcpp (>= 0.12.9), RcppArmadillo, RcppEigen (>= 0.3.3.0)
VignetteBuilder
knitr
SystemRequirements
C++11
RoxygenNote
6.0.1
ByteCompile
true
NeedsCompilation
yes
Packaged
2017-07-12 07:49:47 UTC; jouni
Repository
CRAN
Date/Publication
2017-07-12 14:26:08 UTC

install.packages('walker')

0.2.0

3 months ago

Jouni Helske

GPL (>= 2)

Depends on

R (>= 3.0.2), Rcpp (>= 0.12.9), bayesplot, rstan (>= 2.16.2)

Imports

dplyr, ggplot2, KFAS, methods

Suggests

diagis, gridExtra, knitr (>= 1.11), rmarkdown (>= 0.8.1), testthat

Discussions