The Inverse Lomax-G Family with application to Breaking Strength Data

Autor: Sani I. Doguwa, Jamilu Yunusa Falgore
Rok vydání: 2020
Předmět:
Zdroj: Asian Journal of Probability and Statistics. :49-60
ISSN: 2582-0230
DOI: 10.9734/ajpas/2020/v8i230204
Popis: We proposed a new class of distributions with two additional positive parameters called the Inverse Lomax-G (IL-G) class. A special case was discussed, by taking Weibull as a baseline. Different properties of the new family that hold for any type of baseline model are derived including moments, moment generating function, entropy for Renyi, entropy for Shanon, and order statistics. The performances of the maximum likelihood estimates of the parameters of the sub-model of the Inverse Lomax-G family were evaluated through a simulation study. Application of the sub-model to the Breaking strength data clearly showed its superiority overthe other competing models.
Databáze: OpenAIRE