kl_dist_def

wgt1

<p>Calculates Kullback-Liebler Divergence for two weight vectors.</p>


Provides both parametric and non-parametric estimates of the
correlates of some desired
outcome (e.g. test scores, income) using a new method proposed by
Danieli, Devi and Fryer (2019). This method relaxes the assumption
that one can alter individual characteristics in any way the data
suggest is optimal, and so can be used anytime one wants to use observational
data to better optimize social experiments designed to increase some desired
outcome.

Elad Guttman

optinterv

kl_dist_def: Kullback-Leibler Divergence

Description

Usage

Arguments

Value