hmclearn: Fit Statistical Models Using Hamiltonian Monte Carlo

Provide users with a framework to learn the intricacies of the Hamiltonian Monte Carlo algorithm with hands-on experience by tuning and fitting their own models. All of the code is written in R. Theoretical references are listed below:. Neal, Radford (2011) "Handbook of Markov Chain Monte Carlo" ISBN: 978-1420079418, Betancourt, Michael (2017) "A Conceptual Introduction to Hamiltonian Monte Carlo" <doi:10.48550/arXiv.1701.02434>, Thomas, S., Tu, W. (2020) "Learning Hamiltonian Monte Carlo in R" <doi:10.48550/arXiv.2006.16194>, Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013) "Bayesian Data Analysis" ISBN: 978-1439840955, Agresti, Alan (2015) "Foundations of Linear and Generalized Linear Models ISBN: 978-1118730034, Pinheiro, J., Bates, D. (2006) "Mixed-effects Models in S and S-Plus" ISBN: 978-1441903174.

Version:	0.0.5
Depends:	R (≥ 3.6)
Imports:	bayesplot, parallel, MASS, mvtnorm
Suggests:	knitr, rmarkdown, Matrix, lme4, carData, mlbench, ggplot2, mlmRev, testthat, MCMCpack
Published:	2020-10-05
Author:	Samuel Thomas [cre, aut], Wanzhu Tu [ctb]
Maintainer:	Samuel Thomas <samthoma at iu.edu>
License:	GPL-3
NeedsCompilation:	no
Language:	en-US
Materials:	README NEWS
CRAN checks:	hmclearn results

Documentation:

Reference manual:	hmclearn.pdf
Vignettes:	linear_mixed_effects_hmclearn linear_regression_hmclearn logistic_mixed_effects_hmclearn logistic_regression_hmclearn poisson_regression_hmclearn

Downloads:

Package source:	hmclearn_0.0.5.tar.gz
Windows binaries:	r-devel: hmclearn_0.0.5.zip, r-release: hmclearn_0.0.5.zip, r-oldrel: hmclearn_0.0.5.zip
macOS binaries:	r-release (arm64): hmclearn_0.0.5.tgz, r-oldrel (arm64): hmclearn_0.0.5.tgz, r-release (x86_64): hmclearn_0.0.5.tgz, r-oldrel (x86_64): hmclearn_0.0.5.tgz
Old sources:	hmclearn archive

Linking:

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