STATISTICAL TESTS OF NONPARAMETRIC HYPOTHESES

Focusing on the asymptotic theory of optimal nonparametric tests, this book explores Neyman Pearson and LeCam's theories, alongside empirical processes and kernel estimators. It delves into the asymptotic behavior of tests related to distribution functions, densities, and nonparametric models. The text introduces new test statistics for smooth curves, emphasizing kernel estimators with bias corrections and weak convergence. Additionally, it extends to semiparametric models, incorporating tests derived from continuously observed processes and cumulative interval observations.