EDF Tests for Normality in Linear Models After A Box-Cox Transformation

Abstract

The Box-Cox transformation procedure has been used extensively in data analysis, for example in regression, where the response variable is subjected to a suitable power transformation so that the standard normal-theory linear regression models can be fitted to the transformed values. In this paper, distribution theory is developed for a family of EDF statistics, including the Anderson-Darling statistic A2 and the Cramer-von Mises statistic W2, so that these statistics can be used to test for normality in the linear model after applying the Box-Cox transformation. A table of asymptotic critical points is given for A2 and W2 and numerical examples are given to illustrate the use of the table.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jul 02, 1993
Accession Number
ADA269068

Entities

People

  • Gemai Chen
  • Michael A. Stephens
  • Richard Lockhart

Organizations

  • Stanford University

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Covariance
  • Data Analysis
  • Data Mining
  • Data Science
  • Distribution Functions
  • Distribution Theory
  • Equations
  • Gaussian Processes
  • Information Science
  • Integral Equations
  • Integrals
  • Normal Distribution
  • Random Variables
  • Statistical Algorithms
  • Statistics
  • Theorems
  • United States

Fields of Study

  • Mathematics

Readers

  • Statistical inference.