Code supporting “Bayesian Generalized Horseshoe Estimation of Generalized Linear Models”
Paper published in the Proceedings of the European Conference on Machine Learning, September, 2019.
The code required to recreate the experimental results presented in this paper is available in download form from here. The main folder contains a branch of the Bayesreg package which implements the following additional functionality:
- Poisson regression using the mGrad-1, mGrad-2, pre-conditioned Crank-Nicolson and generalized elliptical slice sampling algorithms;
- binomial regression using the mGrad-1 and mGrad-2 samplers;
- generalized horseshoe priors using the rejection sampler, inverse gamma-inverse gamma and gamma-gamma samplers.
The experiments\ subfolder contains the MATLAB and R scripts (for the NUTS sampler using RStan) required to run the experiments and recreate Tables 2 and 3 in the paper. Note, the paper was produced using a Surface Pro 2016, so timings may (will) vary depending on the particular hardware you are using.