Check and Extend statsmodels for pure Maximum Likelihood Estimators
Currently every model is estimated with linear least squares or iterative least squares.
I would like to add models for which the main estimator is Maximum Likelihood, e.g. a multinomial logit
Where can this be added to the current model structure? What is the appropriate super class? How can we benefit from existing result statistics?
Expand current LikelihoodModel
This is also useful for MLE alternatives to existing estimators, e.g. GLSAR, and also for non-linear MLE, similar to scipy.interpola
Proposed approach: get simple example to work with existing framework, then use it, eg. for a rewrite of mlogit_class.
Blueprint information
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