Alpha-Power Transformed Lindley Distribution: Properties and Associated Inference with Application to Earthquake Data

Sanku Dey, Indranil Ghosh and Devendra Kumar ()
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Sanku Dey: St. Anthony’s College
Indranil Ghosh: University of North Carolina
Devendra Kumar: Central University of Haryana

Annals of Data Science, 2019, vol. 6, issue 4, No 2, 623-650

Abstract: Abstract The Lindley distribution has been generalized by many authors in recent years. A new two-parameter distribution with decreasing failure rate is introduced, called Alpha Power Transformed Lindley (APTL, in short, henceforth) distribution that provides better fits than the Lindley distribution and some of its known generalizations. The new model includes the Lindley distribution as a special case. Various properties of the proposed distribution, including explicit expressions for the ordinary moments, incomplete and conditional moments, mean residual lifetime, mean deviations, L-moments, moment generating function, cumulant generating function, characteristic function, Bonferroni and Lorenz curves, entropies, stress-strength reliability, stochastic ordering, statistics and distribution of sums, differences, ratios and products are derived. The new distribution can have decreasing increasing, and upside-down bathtub failure rates function depending on its parameters. The model parameters are obtained by the method of maximum likelihood estimation. Also, we obtain the confidence intervals of the model parameters. A simulation study is carried out to examine the bias and mean squared error of the maximum likelihood estimators of the parameters. Finally, two data sets have been analyzed to show how the proposed models work in practice.

Keywords: Lindley distribution; Moments; Stress-strength reliability; Maximum likelihood estimation; 60E05; 62F10 (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (7)

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DOI: 10.1007/s40745-018-0163-2

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