Derivations for the Families of Generalized Distributions

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dc.contributor.authorOmekam, Ifeyinwa
dc.contributor.authorAdejumo, Adebowale
dc.date.accessioned2023-06-27T10:26:32Z
dc.date.available2023-06-27T10:26:32Z
dc.date.issued2017-12
dc.description.abstractGeneralization of distributions is usually motivated by limitations in characteristics of existing distributions so as to introduce more flexibility and improve goodness of fit. This is done by parameter induction into an existing distribution and therefore remains an approach to generalizing distributions. In this article, families of generalized distributions are generated by sequential application of methods in permutations of five distinct parameter induction methods: Lehmann Alternative 1 (LA1); Lehmann Alternative 2 (LA2); Marshal and Olkin Method (M-OM); α-Power Transformation (APT); and Power Transformation Method (PTM). This is done by taken two methods at a time. Sixteen distinct families of generalized distributions were generated. Some of the families of generalized distributions obtained are already in existence while several others are entirely new.en_US
dc.identifier.citationOmekam, I. V. and Adejumo, A. O. (2017). Derivations for the Families of Generalized Distributions. Anale. Seria Informatică. Journal. 15(2): 105 – 114. Published by "Tibiscus" University of Timişoara, România.en_US
dc.identifier.issn1583-7165
dc.identifier.issn2065-7471
dc.identifier.urihttps://uilspace.unilorin.edu.ng/handle/20.500.12484/11354
dc.language.isoenen_US
dc.publisher"Tibiscus" University of Timişoara, Româniaen_US
dc.subjectGeneralized distributions; Lehmann Alternatives; α-Power Transformation Method; Power Transformation Method; Marshall and Olkin Method.en_US
dc.titleDerivations for the Families of Generalized Distributionsen_US
dc.typeArticleen_US

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