ebal - Entropy Reweighting to Create Balanced Samples
Implements entropy balancing, a data preprocessing procedure described in Hainmueller (2012, <doi:10.1093/pan/mpr025>) 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.
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7.40 score 1 stars 2 dependents 154 scripts 6.1k downloadsKRLS - Kernel-Based Regularized Least Squares
Implements Kernel-based Regularized Least Squares (KRLS), a machine learning method to fit multidimensional functions y = f(x) for regression and classification problems without relying on linearity or additivity assumptions. KRLS finds the best fitting function by minimizing the squared loss of a Tikhonov regularization problem, using Gaussian kernels as radial basis functions. For further details see Hainmueller and Hazlett (2014, <doi:10.1093/pan/mpt019>).
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7.08 score 2 dependents 100 scripts 589 downloads