Add more test statistics to the MNL summary table
smmaurer opened this issue · comments
The summary table for estimation results from the native 'ChoiceModels' estimator is missing a lot of things:
CHOICEMODELS ESTIMATION RESULTS
===================================================================
Dep. Var.: chosen No. Observations:
Model: Multinomial Logit Df Residuals:
Method: Maximum Likelihood Df Model:
Date: Pseudo R-squ.:
Time: Pseudo R-bar-squ.:
AIC: Log-Likelihood: -1,850.771
BIC: LL-Null: -3,211.771
==========================================================================
coef std err z P>|z| Conf. Int.
--------------------------------------------------------------------------
res_price_per_sqft -0.9158 0.041 -22.557
population -3.2580 0.187 -17.389
ave_income_500:income -0.1176 0.002 -55.188
job_500 0.0418 0.010 4.169
renters 2.3650 0.200 11.851
==========================================================================
Top priorities to add are number of observations, p-values, and r-squared, I think, with others as needed or if they are easy?
The existing test statistics come from the mnl_estimate() function (mnl.py#L612), which we haven't done any refactoring of yet, just wrapped with the MultinomialLogit() class.
The summary table is generated here: mnl.py#L338, with the content and format inspired by PyLogit and StatsModels -- but we can adapt it to display whatever we want.
To fill in more fields, we can calculate them here and pass them to the summary_table() function: mnl.py#L313