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Annals of Data Science
Erschienen in: Annals of Data Science 4/2017

21.07.2017

\(\alpha \) Logarithmic Transformed Family of Distributions with Application

verfasst von: Sanku Dey, Mazen Nassar, Devendra Kumar

Erschienen in: Annals of Data Science | Ausgabe 4/2017

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Abstract

In this paper, a new three-parameter distribution, called \(\alpha \) logarithmic transformed generalized exponential distribution (\(\alpha LTGE\)) is proposed. Various properties of the proposed distribution, including explicit expressions for the moments, quantiles, moment generating function, mean deviation about the mean and median, mean residual life, Bonferroni curve, Lorenz curve, Gini index, Rényi entropy, stochastic ordering and order statistics are derived. It appears to be a distribution capable of allowing monotonically increasing, decreasing, bathtub and upside-down bathtub shaped hazard rates depending on its parameters. The maximum likelihood estimators of the unknown parameters cannot be obtained in explicit forms, and they have to be obtained by solving non-linear equations only. The asymptotic confidence intervals for the parameters are also obtained based on asymptotic variance covariance matrix. Finally, two empirical applications of the new model to real data are presented for illustrative purposes.
Vorheriger Artikel Comparisons of Methods of Estimation for the NH Distribution
Nächster Artikel A Feature Selection Method Based on Ranked Vector Scores of Features for Classification

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Metadaten
Titel
Logarithmic Transformed Family of Distributions with Application
verfasst von
Sanku Dey
Mazen Nassar
Devendra Kumar
Publikationsdatum
21.07.2017
Verlag
Springer Berlin Heidelberg
Erschienen in
Annals of Data Science / Ausgabe 4/2017
Print ISSN: 2198-5804
Elektronische ISSN: 2198-5812
DOI
https://doi.org/10.1007/s40745-017-0115-2

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