Plans for the Summer

A quick update on the plans for statsmodels over the next few months.

I have been accepted for my second Google Summer of Code, which means that we will have a chance to make a big push to get a lot of our work out of the sandbox, tested, and included in the main code base.

You can see the roadmap on Google's GSoC site here. You might have to log in to view it.

The quick version follows. As far as general issues, I will be getting the code ready for Python 3 and focusing on some design issues including an improved generic maximum likelihood framework, post-estimation testing, variable name handling, and output in text tables, LaTeX, and html. I will then be working to get a lot of our code out of the sandbox. This includes timeseries convenience functions and models such as GARCH, VARMA, Hodrick-Prescott filter, and a state space model that uses the Kalman filter. I will be polishing the systems of equation framework and panel (longitudinal) data estimators. We have also been working on some nonparametric estimators including univariate kernel density estimators and kernel regression estimators. Finally, as part of my coursework I have been working toward (generalized) maximum entropy models that I hope to include as well as some work on the scipy.maxentropy module.

I will give a quick talk on the project for the SciPy Conference in Austin.

It looks like we are set to make a good deal of progress on the code this summer.