Entropy Reweighting to Create Balanced Samples

Implements entropy balancing, a data preprocessing procedure described in Hainmueller (2012, ) that allows users to reweight a dataset such that the covariate distributions in the reweighted data satisfy a set of user-specified moment conditions. Useful for creating balanced samples in observational studies with a binary treatment where the control group is reweighted to match the covariate moments of the treatment group, and for reweighting a survey sample to known characteristics from a target population.