Nonparametric Estimation: Empirical Likelihood Approach

This lecture covers the nonparametric estimation of constrained distributions using the empirical likelihood approach. It explains how to estimate marginal transformations to the Fréchet scale and the Gumbel scale, as well as the dependence parameter. The lecture also delves into the computation of probabilities and the empirical estimation of measures based on data. Additionally, it discusses the maximization of nonparametric likelihood and the consistency of estimators in different dimensions.