doi:10.1016/j.softx.2022.101016>). Gaussian, Poisson, and binomial observations are supported. The Markov chain Monte Carlo (MCMC) 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. For non-Gaussian models, the package uses the importance sampling type estimators based on approximate marginal MCMC as in Vihola, Helske, Franks (2020, <doi:10.1111/sjos.12492>).">

walker: Bayesian Generalized Linear Models with Time-Varying Coefficients (original) (raw)

Efficient Bayesian generalized linear models with time-varying coefficients as in Helske (2022, <doi:10.1016/j.softx.2022.101016>). Gaussian, Poisson, and binomial observations are supported. The Markov chain Monte Carlo (MCMC) 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. For non-Gaussian models, the package uses the importance sampling type estimators based on approximate marginal MCMC as in Vihola, Helske, Franks (2020, <doi:10.1111/sjos.12492>).

Version: 1.0.10
Depends: bayesplot, R (≥ 3.4.0), rstan (≥ 2.26.0)
Imports: coda, dplyr, Hmisc, ggplot2, KFAS, loo, methods, Rcpp (≥ 0.12.9), RcppParallel, rlang, rstantools (≥ 2.0.0)
LinkingTo: BH (≥ 1.66.0), Rcpp (≥ 0.12.9), RcppArmadillo, RcppEigen (≥ 0.3.3.3.0), RcppParallel, rstan (≥ 2.26.0), StanHeaders (≥ 2.26.0)
Suggests: diagis, gridExtra, knitr (≥ 1.11), rmarkdown (≥ 0.8.1), testthat
Published: 2024-08-30
DOI: 10.32614/CRAN.package.walker
Author: Jouni Helske ORCID iD [aut, cre]
Maintainer: Jouni Helske <jouni.helske at iki.fi>
BugReports: https://github.com/helske/walker/issues
License: GPL (≥ 3)
URL: https://github.com/helske/walker
NeedsCompilation: yes
SystemRequirements: GNU make
Citation: walker citation info
Materials: README
CRAN checks: walker results

Documentation:

Downloads:

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=walkerto link to this page.