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.


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install.packages("walker")

0.2.0 by Jouni Helske, 4 months ago


Browse source code at https://github.com/cran/walker


Authors: Jouni Helske


Documentation:   PDF Manual  


GPL (>= 2) license


Imports dplyr, ggplot2, KFAS, methods

Depends on Rcpp, bayesplot, rstan

Suggests diagis, gridExtra, knitr, rmarkdown, testthat

Linking to StanHeaders, rstan, BH, Rcpp, RcppArmadillo, RcppEigen

System requirements: C++11


See at CRAN