Accession Number : ADA293875
Title : A New Goodness-of-Fit Test for the Gamma Distribution Based on Sample Spacings from Complete and Censored Samples.
Descriptive Note : Master's thesis,
Corporate Author : AIR FORCE INST OF TECH WRIGHT-PATTERSON AFB OH SCHOOL OF ENGINEERING
Personal Author(s) : Duman, Huseyin
PDF Url : ADA293875
Report Date : MAR 1995
Pagination or Media Count : 168
Abstract : This thesis studies a new goodness-of-fit test for the gamma distribution with known shape parameter. This test statistic, Z*, is based on spacings from complete or censored samples. The size of samples varied between 5 and 35. The critical value tables were generated for the Z* test statistic for complete and censored samples. The critical values were obtained for five different significance levels: 0.20 0.15, 0.10, 0.05, and 0.01. An extensive power study, containing 50,000 Monte Carlo runs was conducted using nine alternative distributions, H(a). It was observed that the Z* test statistic was more powerful against certain alternatives which are less skewed than the gamma distribution with a given shape parameter. A regression between the critical values and the sample size, shape parameter, significance levels and degree of censoring was established. The power of the Z* test statistic is compared to the powers of the competing test statistics (K-S, W sub 2, and A-D). This thesis reveals that the Z* test statistic is a directional test. This feature may be utilized to attain higher power values by coupling the Z* and the A-D test statistics in a sequential test. (AN)
Descriptors : *MONTE CARLO METHOD, *GOODNESS OF FIT TESTS, MATHEMATICAL MODELS, COMPUTERIZED SIMULATION, WEIBULL DENSITY FUNCTIONS, PARAMETERS, MAXIMUM LIKELIHOOD ESTIMATION, PROBABILITY DISTRIBUTION FUNCTIONS, COMPARISON, STATISTICAL DATA, THESES, MATHEMATICAL PROGRAMMING, REGRESSION ANALYSIS, FORTRAN, SAMPLING, HYPOTHESES, CHI SQUARE TEST, DISTRIBUTION FUNCTIONS.
Subject Categories : Statistics and Probability
Distribution Statement : APPROVED FOR PUBLIC RELEASE