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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "BayesRTMB" in publications use:'
type: software
license: MIT
title: 'BayesRTMB: Bayesian Inference Using ''RTMB'''
version: 0.1.1
doi: 10.32614/CRAN.package.BayesRTMB
abstract: 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) <https://doi.org/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>.
authors:
- family-names: Shimizu
  given-names: Hiroshi
  email: simizu706@gmail.com
repository: https://norimune.r-universe.dev
repository-code: https://github.com/norimune/BayesRTMB
commit: 1baeafa3b43e993fb8e221056728524510e1eef4
url: https://norimune.github.io/BayesRTMB/
date-released: '2026-05-28'
contact:
- family-names: Shimizu
  given-names: Hiroshi
  email: simizu706@gmail.com