A Modified Anderson Darling Goodness-of-Fit Test for the Gamma Distribution with Unknown Scale and Location Parameters

Abstract

A new modified Anderson-Darling goodness-of-fit test is introduced for the three-parameter Gamma distribution when the location parameter is found by minimum distance estimation and scale parameter by maximum likelihood estimation. Monte Carlo simulation studies were performed to calculate the critical values for A-D test when A-D statistic is minimized. These critical values are then used for testing whether a set of observations follows a Gamma distribution when the scale and location parameters axe unspecified and are estimated from the sample. Functional relationship between the critical values of A-D is also examined for each shape parameter by the variables, sample size (n) and significance level (a). The power study is performed with the hypothesized Gamma against alternate distributions. Comparison with the previous study which uses MLEs for location and scale showed that the modified test is better in most cases.... Gamma distribution, Goodness-of-fit, Monte Carlo simulation, Anderson-Darling, Minimum distance, Maximum likelihood, Parameter estimation.

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Document Details

Document Type
Technical Report
Publication Date
Mar 08, 1993
Accession Number
ADA262486

Entities

People

  • Tamer Ozmen

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Computational Science
  • Computer Programs
  • Data Mining
  • Data Science
  • Distribution Functions
  • Information Science
  • Knowledge Management
  • Maximum Likelihood Estimation
  • Monte Carlo Method
  • Probabilistic Models
  • Probability
  • Probability Density Functions
  • Probability Distributions
  • Random Variables
  • Reliability
  • Statistical Algorithms
  • Statistical Analysis

Fields of Study

  • Mathematics

Readers

  • Statistical inference.