2016
DOI: 10.17654/jpjbdec2015_137_167
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Modified Goodness of Fit Tests for Flexible Weibull Distribution Based on Type-Ii Censoring Schemes

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“…The paper uses this test for unspecified parameters (i.e., parameters estimated from the data) and various distributions. There, the p-value corresponding to the test statistic was estimated from simulations [86,87], computing cvm(sample, CDF 1 ) from random samples drawn from the hypothesized distribution CDF and using the distribution CDF 1 with best fit parameters for the sample. (This method is implemented in the Mathematica function DistributionFitTest using the Monte-Carlo method.)…”
Section: Distribution Fit Testsmentioning
confidence: 99%
“…The paper uses this test for unspecified parameters (i.e., parameters estimated from the data) and various distributions. There, the p-value corresponding to the test statistic was estimated from simulations [86,87], computing cvm(sample, CDF 1 ) from random samples drawn from the hypothesized distribution CDF and using the distribution CDF 1 with best fit parameters for the sample. (This method is implemented in the Mathematica function DistributionFitTest using the Monte-Carlo method.)…”
Section: Distribution Fit Testsmentioning
confidence: 99%