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 |

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_0.0.5.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: hmclearn_0.0.5.tgz, r-oldrel: hmclearn_0.0.5.tgz |

Old sources: | hmclearn archive |

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