pgdraw-package: The pgdraw package
In pgdraw: Generate Random Samples from the Polya-Gamma Distribution

Description Details Note Author(s) References See Also

This package contains a function to generates random samples from the Polya-Gamma distribution using an implementation of the algorithm described in J. Windle's PhD thesis. A frequent application of this distribution is in Bayesian analysis of logistic regression models.

The underlying implementation is in C.

For usage, see the examples in pgdraw and pgdraw.moments.

To cite this package please reference:

Makalic, E. & Schmidt, D. F. High-Dimensional Bayesian Regularised Regression with the BayesReg Package arXiv:1611.06649 [stat.CO], 2016 https://arxiv.org/pdf/1611.06649.pdf

A MATLAB-compatible implementation of the sampler in this package can be obtained from:

http://dschmidt.org/?page_id=189

Daniel Schmidt daniel.schmidt@monash.edu

Faculty of Information Technology, Monash University, Australia

Enes Makalic emakalic@unimelb.edu.au

Centre for Epidemiology and Biostatistics, The University of Melbourne, Australia

Jesse Bennett Windle Forecasting High-Dimensional, Time-Varying Variance-Covariance Matrices with High-Frequency Data and Sampling Polya-Gamma Random Variates for Posterior Distributions Derived from Logistic Likelihoods PhD Thesis, 2013

Bayesian Inference for Logistic Models Using Polya-Gamma Latent Variables Nicholas G. Polson, James G. Scott and Jesse Windle Journal of the American Statistical Association Vol. 108, No. 504, pp. 1339–1349, 2013

Chung, Y.: Simulation of truncated gamma variables Korean Journal of Computational & Applied Mathematics, 1998, 5, 601-610

pgdraw, pgdraw.moments

pgdraw documentation built on May 1, 2019, 9:22 p.m.