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A New Goodness-Of-Fit Test For The Gamma Distribution Based On Sample Spacings From Complete And Censored Samples, Huseyin Duman
A New Goodness-Of-Fit Test For The Gamma Distribution Based On Sample Spacings From Complete And Censored Samples, Huseyin Duman
Theses and Dissertations
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, Ha. It was observed that the Z* test statistic was more powerful against certain …
Modified Goodness-Of-Fit Tests For The Inverse Gaussian Distribution With Two Unknown Parameter, Huseyin Gunes
Modified Goodness-Of-Fit Tests For The Inverse Gaussian Distribution With Two Unknown Parameter, Huseyin Gunes
Theses and Dissertations
Modified Kolmogorov- Smirnov (KS), Anderson-Darling (AD), Cramer-von Mises (CV), Kupier (V), and Watson (W) goodness-of-fit tests are generated for the inverse Gaussian distribution with unknown parameters. The inverse Gaussian parameters are estimated by maximum likelihood estimation. A Monte Carlo simulation of 50,000 repetitions is used to generate critical values for sample sizes of 5 through 50 with an increment of five, sample sizes of 60 through 100 with an increment of 10, and 24 different values of the inverse Gaussian shape parameter. A 50,000-repetition Monte Carlo power study is carried out using data with sample sizes of 5 through 100 …