Hung Q. Ngo

Would support for logistic regression with l1-regularization be part of this issue (special case of Bayesian GLM), or should it be a separate issue? (Here's [an algorithm](https://www.aaai.org/Papers/AAAI/2006/AAAI06-064.pdf).)

Perhaps instead of going full-blown Bayesian, support for elastic net regularization would be great. The choices of [features](http://docs.h2o.ai/h2o/latest-stable/h2o-docs/booklets/GLMBooklet.pdf) included with H2O.ai's GLM implementation seems to be practical.

@Nosferican what are the last kinks? I'm learning Julia, and have great interest in GLMs and their generalization, so I'd love to help out if my speed doesn't interfere with...

@Nosferican juding from your comment [here](https://discourse.julialang.org/t/two-questions-about-glm/10376/3), *ordinal* LR is not yet supported, right? Because you mentioned something about `isordered` for `LogitLink` which I couldn't parse.

@Nosferican : i've read enough (about VGLM & Julia) to understand your code. Is the one in gist the latest version? Do you need help with anything else? In addition...

@Nosferican : any update on your vector GLM implementation? I am thinking of working on ordinal regression and that would benefit from VGLM tremendously

got it. I'm busy with things at work for a few days, will get back to reading/trying this out as soon as I can. Thanks for the update.