Dear all, I am pleased to announce Autologistic.jl, a package for autologistic regression (ALR) modelling. The ALR model is an extension of logistic regression. It’s a probabilistic graphical model for binary responses (including covariate effects).
Some important features of the package:
- Analyze ALR models with arbitrary graphs.
- Estimation and inference using maximum likelihood for small models, or pseudolikelihood + parametric bootstrap for larger models.
- Includes different variants of the ALR model (change the numeric coding of the responses, or use different forms of centering).
- Extensible design to allow different parametrizations of the model.
- Draw random samples from the models using Gibbs sampling or several different perfect sampling implementations.
This is my first serious project in Julia, after many years working with R and MATLAB. I have to say the experience of developing in Julia has been very positive, especially considering that Julia is still a “new” language. And in the end my samplers run well over 100x faster than they did in MATLAB. So hats off to everyone in the Julia community, I’m a convert.