You can find my GitHub page here.

Gshape.jl provides a fast and simple algorithm for approximating the full conditional distribution of the shape parameter of a gamma distribution, using a gamma distribution for the approximation. See the article for details:

Fast and accurate approximation of the full conditional for gamma shape parameters, J. W. Miller, 2018. (pdf)

BayesianMixtures is a Julia package for nonparametric Bayesian mixture models and Bayesian clustering. The following model types are currently implemented:

The following component distributions are currently implemented: For all models, inference is performed using the Jain-Neal split-merge samplers. For MFMs, this is done using the results from our article:

Mixture models with a prior on the number of components, J. W. Miller and M. T. Harrison, Journal of the American Statistical Association (JASA), Vol. 113, 2018, pp. 340-356. (pub) (pdf) (arXiv)

Click here for more information and for downloading.

EXACT is a software package for exact counting and exact sampling of binary or non-negative integer matrices with specified row and column sums. (Download version 0.3 here.) Note: This program is only applicable for matrices of moderate size — smaller than 40x40 or so — or very sparse larger matrices. The program can be very memory intensive, so if you give it a problem that is too difficult, it will probably allocate all of your available RAM and then get bogged down (so you might want to keep an eye on how much RAM it's using).

For larger matrices, we provide a sequential importance sampling algorithm that is very efficient and often is very close to exact. A Matlab implementation of this is available in the folder \examples\total variation distance of the EXACT package.

Features Applications References

Exact sampling and counting for fixed-margin matrices, J. W. Miller and M. T. Harrison, The Annals of Statistics, Vol. 41, No. 3, 2013, pp. 1569-1592. (pub) (pdf) (arXiv)

Importance sampling for weighted binary random matrices with specified margins, M. T. Harrison and J. W. Miller, (In preparation). (pdf) (arXiv)