2.  Gronau, Quentin F; Singmann, Henrik; Wagenmakers, EricJan bridgesampling: An R Package for Estimating Normalizing Constants Journal Article Forthcoming Journal of Statistical Software, Forthcoming. Abstract  Links  BibTeX  Tags: hierarchicalBayesian modeling, R, Software, Statistics  Computation @article{Gronau2020,
title = {bridgesampling: An R Package for Estimating Normalizing Constants},
author = {Quentin F Gronau and Henrik Singmann and EricJan Wagenmakers},
url = {https://arxiv.org/pdf/1710.08162.pdf, preprint
http://arxiv.org/abs/1710.08162, on ArXiV},
year = {2020},
date = {20200924},
urldate = {20180925},
journal = {Journal of Statistical Software},
abstract = {Statistical procedures such as Bayes factor model selection and Bayesian model averaging require the computation of normalizing constants (e.g., marginal likelihoods). These normalizing constants are notoriously difficult to obtain, as they usually involve highdimensional integrals that cannot be solved analytically. Here we introduce an R package that uses bridge sampling (Meng & Wong, 1996; Meng & Schilling, 2002) to estimate normalizing constants in a generic and easytouse fashion. For models implemented in Stan, the estimation procedure is automatic. We illustrate the functionality of the package with three examples.},
keywords = {hierarchicalBayesian modeling, R, Software, Statistics  Computation},
pubstate = {forthcoming},
tppubtype = {article}
}
Statistical procedures such as Bayes factor model selection and Bayesian model averaging require the computation of normalizing constants (e.g., marginal likelihoods). These normalizing constants are notoriously difficult to obtain, as they usually involve highdimensional integrals that cannot be solved analytically. Here we introduce an R package that uses bridge sampling (Meng & Wong, 1996; Meng & Schilling, 2002) to estimate normalizing constants in a generic and easytouse fashion. For models implemented in Stan, the estimation procedure is automatic. We illustrate the functionality of the package with three examples. 
1.  Singmann, Henrik; Kellen, David An introduction to linear mixed modeling in experimental psychology Incollection Forthcoming New Methods in Cognitive Psychology, Psychology Press, Forthcoming. Links  BibTeX  Tags: mixed models, R, Statistics  Computation @incollection{Singmann2020,
title = {An introduction to linear mixed modeling in experimental psychology},
author = {Henrik Singmann and David Kellen},
url = {http://singmann.org/download/publications/singmann_kellenintroductionmixedmodels.pdf, preprint},
year = {2020},
date = {20200901},
booktitle = {New Methods in Cognitive Psychology},
publisher = {Psychology Press},
keywords = {mixed models, R, Statistics  Computation},
pubstate = {forthcoming},
tppubtype = {incollection}
}
