We have updated *bayesreg, *a MATLAB toolbox that implements Bayesian linear and logistic regression with sparsity-inducing priors, to version 1.3. The new version can be downloaded here.

Version 1.3 includes the following changes:

- Tidied up the summary display to switch between scientific and normal notation depending

on size of numbers in table - Fixed the summary banner to adjust to the size of the table
- Added support for MATLAB tables
- Code now accepts either X/y as matrix/vector, or table/string name of variable to use as table

- Added support for categorical predictors
- These are now either specified using ‘catvars’ option for matrix inputs, or automatically determined from the contents of the table

- Removed the dependency of br_summary() on X and y
- Consolidated all likelihood functions into a single br_regnlike() function that is vectorized using bsxfun
- Added a br_predict function to produce predictions over data given design matrices
- Checks input design matrix/table against structure of training data
- Automatically handles categorical expansions as required
- Produces credible intervals if requested
- Produces prediction statistics if targets are supplied

- Updated and improved the example scripts
- Added initial internal code structures required for grouping variables and variable expansions
- Fix bug in computation of R2