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AuthorPakyari, Reza
Available date2022-01-31T11:16:07Z
Publication Date2021-06-16
Publication NameCommunications in Statistics - Simulation and Computation
Identifierhttp://dx.doi.org/10.1080/03610918.2021.1930052
CitationReza Pakyari (2021): Goodness-of-fit testing based on Gini Index of spacings for progressively Type-II censored data, Communications in Statistics - Simulation and Computation, DOI: 10.1080/03610918.2021.1930052
URIhttp://hdl.handle.net/10576/26221
AbstractIn this article, we propose two new scale invariant test statistics when the available data are subject to progressively Type-II censoring. The proposed tests are based on Gini index of spacings. It is observed thorough extensive Monte Carlo simulations that the proposed tests are quite powerful in compare to similar existing goodness-of-fit tests studied by Balakrishnan et al. and Wang. We also illustrate the method proposed here using a real data from reliability literature.
Languageen
PublisherTaylor & Francis
SubjectExponential distribution
Gini index
Goodness-of-fit testing
Monte Carlo simulation
Order statistics
Progressive Type-II censoring
Spacings
TitleGoodness-of-fit testing based on Gini Index of spacings for progressively Type-II censored data
TypeArticle
dc.accessType Open Access


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