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walker  

Bayesian Generalized Linear Models with Time-Varying Coefficients
View on CRAN: Click here


Download and install walker package within the R console
Install from CRAN:
install.packages("walker")

Install from Github:
library("remotes")
install_github("cran/walker")

Install by package version:
library("remotes")
install_version("walker", "1.0.8")



Attach the package and use:
library("walker")
Maintained by
Jouni Helske
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-06-15
Latest Update: 2023-08-08
Description:
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>).
How to cite:
Jouni Helske (2017). walker: Bayesian Generalized Linear Models with Time-Varying Coefficients. R package version 1.0.8, https://cran.r-project.org/web/packages/walker
Previous versions and publish date:
0.1.0 (2017-06-15 17:18), 0.2.0 (2017-07-12 16:26), 0.2.1 (2018-01-09 18:27), 0.2.2 (2018-10-16 21:50), 0.2.3-1 (2018-11-09 15:30), 0.2.3 (2018-10-23 14:10), 0.2.4-1 (2019-02-25 13:50), 0.2.4 (2019-02-15 17:00), 0.2.5 (2019-03-04 14:50), 0.3.0 (2019-09-22 15:00), 0.3.1-1 (2020-01-23 16:50), 0.4.0 (2020-05-15 20:20), 0.4.1-3 (2020-08-14 12:10), 0.5.0 (2020-10-19 15:20), 1.0.1-1 (2021-01-31 01:20), 1.0.1 (2021-01-25 11:40), 1.0.2 (2021-04-06 18:10), 1.0.3-1 (2022-01-31 13:10), 1.0.3 (2021-09-11 10:10), 1.0.4 (2022-03-03 16:00), 1.0.6-1 (2022-10-16 22:00), 1.0.7 (2023-08-09 01:10)
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