Modified Goodness of Fit Tests for the Burr Distribution with Two Unknown Shape Parameters | ||||
| The Egyptian Statistical Journal | ||||
| Article 5, Volume 38, Issue 1, June 1994, Page 115-128 | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/esju.1994.314819 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
| Samir K. Ashour; Abd-Allah M. Abd-Elfattah | ||||
| Abstract | ||||
| Goodness of fit tests are designed for checking the validity of a null hypothesis. This hypothesis is a statement about the form of the distribution function of the parent population from which the sample is drawn. Ideally, the hypothesized distribution is completely specified, if the hypothesis states that the distribution belong to some family of distributions. The unknown parameters must be estimated from the sample data in order to perform a test. For censored samples, the complete sample procedures of goodness of fit tests and the critical values obtained from published tables of the distributions of the test statistics based on complete samples are inappropriate. Also, the goodness of fit tests for censored data are inappropriate when parameters of the hypothesized distribution are estimated from the data used for the test. This paper gives tables of critical values of modified Kolmogorov-Smirnov (KS). Cramer-Von Mises (CVM) and Anderson-Darling (AD) tests for the Burr distribution with unknown parameters in the case of type Il censored samples. The powers of these tests are given for a number of alternative distributions. | ||||
| Keywords | ||||
| Burr Distribution; Censored Samples; Critical Values Tables; Modified Goodness of Fit Tests | ||||
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Statistics Article View: 22 |
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