ABSTRACT

Illustrating a simple, novel method for solving an array of statistical problems, Observed Confidence Levels: Theory and Application describes the basic development of observed confidence levels, a methodology that can be applied to a variety of common multiple testing problems in statistical inference. It focuses on the modern nonparametric

chapter 1|22 pages

Introduction

chapter 2|46 pages

Single Parameter Problems

chapter 3|34 pages

Multiple Parameter Problems

chapter 4|38 pages

Linear Models and Regression

chapter 5|52 pages

Nonparametric Smoothing Problems

chapter 6|20 pages

Further Applications

chapter 7|22 pages

Connections and Comparisons