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2015
Journal Article
Title
Data transformations and goodness-of-fit tests for type-II right censored samples
Abstract
We suggest several goodness-of-fit (GOF) methods which are appropriate with Type-II right censored data. Our strategy is to transform the original observations from a censored sample into an approximately i.i.d. sample of normal variates and then perform a standard GOF test for normality on the transformed observations. A simulation study with several well known parametric distributions under testing reveals the sampling properties of the methods. We also provide theoretical analysis of the proposed method.