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" <arXiv:1701.02434>, Thomas, S., Tu, W. (2020) "Learning Hamiltonian Monte Carlo in R" <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
Old sources: hmclearn archive

Linking:

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