A Study of the Properties of a New Goodness-of-Fit Test

Abstract

We investigate the power properties of a new goodness-of-fit test proposed by Foutz (1980). This new test is compared with the Chi squared test and the Kolmogorov-Smirnov (K-S) test for normality when the samples come from (1) the family of asymmetric stable distributions, (2) mixture of normal distributions, and (3) the Pearson family. The general conclusion is that the new test performs better than the Chi squared and the K-S test when the parent distribution is heavy tailed. If the hypothesized distribution differs from the true distribution in location only, the new test does not do as well as the other two.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
May 01, 1980
Accession Number
ADA086563

Entities

People

  • Richard Franke
  • Toke Jayachandran

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Data Science
  • Distribution Functions
  • Goodness Of Fit Tests
  • Information Science
  • Mathematics
  • Military Research
  • Monte Carlo Method
  • Normal Distribution
  • Numerical Integration
  • Order Statistics
  • Precision
  • Probability
  • Security
  • Sequences
  • Simulations
  • Statistical Analysis
  • Statistics

Fields of Study

  • Mathematics

Readers

  • Statistical inference.