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: 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: | 0.0.4 |
| Depends: | R (≥ 3.6) |
| Imports: | bayesplot, parallel, MASS, mvtnorm |
| Suggests: | knitr, rmarkdown, Matrix, lme4, carData, mlbench, ggplot2, mlmRev, testthat, MCMCpack |
| Published: | 2020-07-27 |
| 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 |
| Reference manual: | hmclearn.pdf |
| Vignettes: |
linear_mixed_effects_hmclearn linear_regression_hmclearn logistic_mixed_effects_hmclearn logistic_regression_hmclearn poisson_regression_hmclearn |
| Package source: | hmclearn_0.0.4.tar.gz |
| Windows binaries: | r-devel: hmclearn_0.0.4.zip, r-release: hmclearn_0.0.4.zip, r-oldrel: hmclearn_0.0.4.zip |
| macOS binaries: | r-release: hmclearn_0.0.4.tgz, r-oldrel: hmclearn_0.0.4.tgz |
| Old sources: | hmclearn archive |
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