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Erschienen in: Quality & Quantity 1/2019

29.05.2018

A size-biased Ishita distribution and application to real data

verfasst von: Amer Ibrahim Al-Omari, Amjad D. Al-Nasser, Enrico Ciavolino

Erschienen in: Quality & Quantity | Ausgabe 1/2019

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Abstract

The present paper offers a new extension to the Ishita distribution called Size-Biased Ishia distribution (SBID). Various structural statistical properties of this distribution are derived such as the jth moment, moment generating function, the coefficients of variation, skewness and kurtosis. Also, the distribution of order statistics, harmonic mean, mode, reliability analysis, maximum likelihood estimation are provided, as well as the Fisher’s information, generalized and Renyi entropies are derived. The main advantage of using sized-based distributions appears when the sample are recorded with unequal probabilities. Accordingly, the superiority of the SBI distribution is illustrated to ball bearings data. It is shown that the SBID is the most appropriate model for this data set as compared to Rama distribution, Ishita distribution and Marshall–Olkin Esscher Transformed Laplace distribution. We believe that the SBID is an alternative distribution to lifetime data analysis.

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Metadaten
Titel
A size-biased Ishita distribution and application to real data
verfasst von
Amer Ibrahim Al-Omari
Amjad D. Al-Nasser
Enrico Ciavolino
Publikationsdatum
29.05.2018
Verlag
Springer Netherlands
Erschienen in
Quality & Quantity / Ausgabe 1/2019
Print ISSN: 0033-5177
Elektronische ISSN: 1573-7845
DOI
https://doi.org/10.1007/s11135-018-0765-y

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