Please use this identifier to cite or link to this item: https://research.matf.bg.ac.rs/handle/123456789/1876
Title: Univariate goodness-of-fit tests for randomly censored data: tests' adaptation versus data transformation
Authors: Milošević, Bojana 
Cuparić, Marija 
Affiliations: Probability and Mathematical Statistics 
Probability and Mathematical Statistics 
Rank: M34
Publisher: Ljubljana : Statistično društvo Slovenije
Related Publication(s): 17th Applied Statistics
Conference: Applied Statistics(17 ; 2021)
Abstract: 
Recently, several approaches for adaptation of goodness of fit tests for censored data have been proposed. This paved the way for the bunch of goodness of tests for such data. However, those tests usually depends on censoring distribution which is unknown in practice, and the application of resampling procedures is indispensable, but computationally expensive, step toward obtaining p-values. Here, we present an imputation procedure that can serve as an alternative approach to adaptation proposal. Additionally, we illustrate proposal on several characterization based exponentiality tests proposed so far.
URI: https://research.matf.bg.ac.rs/handle/123456789/1876
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