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BayesRTMB  

Bayesian Inference Using 'RTMB'
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("BayesRTMB", "0.1.1")



Attach the package and use:
library("BayesRTMB")
Maintained by
Hiroshi Shimizu
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-06-01
Latest Update: 2026-06-01
Description:
Provides tools for Markov chain Monte Carlo (MCMC) and Maximum A Posteriori (MAP) estimation utilizing the 'RTMB' package. It supports various statistical models including generalized linear mixed models, factor analysis, item response theory, and multidimensional unfolding. The package allows users to easily transition between frequentist and Bayesian paradigms using a unified interface. Automatic differentiation and Laplace approximation follow Kristensen et al. (2016) <doi:10.18637/jss.v070.i05>, and MCMC sampling uses the No-U-Turn Sampler described by Hoffman and Gelman (2014) <https://jmlr.org/papers/v15/hoffman14a.html>.
How to cite:
Hiroshi Shimizu (2026). BayesRTMB: Bayesian Inference Using 'RTMB'. R package version 0.1.1, https://cran.r-project.org/web/packages/BayesRTMB. Accessed 05 Aug. 2026.
Previous versions and publish date:
0.1.1 (2026-06-01 10:40), 0.2.1 (2026-06-23 12:30), 0.2.3 (2026-07-13 11:00), (2026-07-24 09:30)
Other packages that cited BayesRTMB R package
View BayesRTMB citation profile
Other R packages that BayesRTMB depends, imports, suggests or enhances
Complete documentation for BayesRTMB
Functions, R codes and Examples using the BayesRTMB R package
Full BayesRTMB package functions and examples
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