2015
DOI: 10.2991/jsta.2015.14.3.4
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A Lifetime Distribution Based on a Transformation of a Two-Sided Power Variate

Abstract: We introduce a new generalization of Weibull distribution by making use of a transformation of the standard two-sided power distributed random variable. Weibull and the exponentiated Weibull distributions are submodels of this new distribution. We show that this newly defined distribution is in fact a mixture of the truncated forms of Weibull and the exponentiated Weibull distributions. The new distribution has two shape parameters that make it more flexible for modeling data than Weibull and exponentiated Wei… Show more

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Cited by 10 publications
(6 citation statements)
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“…From the relations, Eqs. (10) and (11) we see that the Kullback Leibler divergence between the TTSG-G and the TSG-G distributions is equal to −H (U). So, this informational measure is free of the parent distribution G.…”
Section: Kullback Leibler Divergencementioning
confidence: 88%
See 1 more Smart Citation
“…From the relations, Eqs. (10) and (11) we see that the Kullback Leibler divergence between the TTSG-G and the TSG-G distributions is equal to −H (U). So, this informational measure is free of the parent distribution G.…”
Section: Kullback Leibler Divergencementioning
confidence: 88%
“…In recent years, a number of researchers have studied some generalization of the TSP distribution such as Nadarajah [5], Oruç and Bairamov [6], Vicari et al [7], Herrerías-Velasco et al [8], and Soltani and Homei [9]. Korkmaz and Genç [10] proposed a new generalization of Weibull distribution by making use of a transformation of the standard TSP distribution. Also, Korkmaz…”
Section: Introductionmentioning
confidence: 99%
“…Additional important generalized forms of the Weibull model are introduced by Korkmaz et al [22][23][24], Abouelmagd et al [25][26][27], Cordeiro et al [28], Bhatti et al [29], Nasir et al [30], Alizadeh et al [31], Afify et al [32,33], Hussein et al [34], Mead et al [35] and Nassar et al [36].…”
Section: Introductionmentioning
confidence: 99%
“…Küchenhoff and Thamerus (1996) used GEV in the extreme value analysis of Munich air pollution data. Ercelebi and Toros (2009) Recently, for modelling air pollution data, Korkmaz (2015) described two-sided generalised Gumbel (TSGG) distribution, which is a special case of GEV (type I distribution). Martins et al (2017) did extreme value modelling of air pollution data and compared results amongst two large urban regions of South America.…”
Section: Introductionmentioning
confidence: 99%