Statistical Inference on 2-Component Mixture of Topp-Leone Distribution, Bayesian and non-Bayesian Estimation

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Kharazmi o.; DEY S.; KUMAR D.

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Journal Paper

Paper Information

Journal: JOURNAL OF MATHEMATICAL EXTENSION Year:2022 | Volume:16 | Issue:9 Page(s): 00-00

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Title

Statistical Inference on 2-Component Mixture of Topp-Leone Distribution, Bayesian and non-Bayesian Estimation

Author(s)

Kharazmi o. | DEY S. | KUMAR D. | Issue Writer Certificate

Keywords

Bayes estimators

Bayesian intervals

Loss functions

Mixture distribution

Posterior risks

Uniform prior

Abstract

To study the heterogeneous nature of lifetimes of certain mechanical or engineering processes, a mixture model of some suitable lifetime distributions may be more appropriate and appealing as com-pared to simple models. This paper considers mixture of Topp-Leone distributions under classical and Bayesian perspective based on com-plete sample. The new distribution which exhibits decreasing and up-side down bathtub shaped density while the distribution has the ability to model lifetime data with decreasing, increasing and upside down bathtub shaped failure rates. We derive several properties of the new distribution such as moments, moment generating function, conditional moment, mean deviation, Bonferroni and Lorenz curves and the order statistics of the proposed distribution. Moreover, we estimate the pa-rameters of the model by using frequentist and Bayesian approaches. For Bayesian analysis, , ve Loss functions, namely the squared error loss function (SELF), weighted squared error loss function (WSELF), mod-i, ed squared error loss function (MSELF), precautionary loss function (PLF), and K-loss function (KLF) and uniform as well as gamma pri-ors are considered to obtain the Bayes estimators and posterior risk of the unknown parameters of the model. Furthermore, credible intervals (CIs) and highest posterior density (HPD) intervals are also obtained. Monte Carlo simulation study is done to access the behavior of these estimators. For the illustrative purposes, a real-life application of the proposed distribution to a tensile strength data set is provided.

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APA: Copy

Kharazmi, o., DEY, S., & KUMAR, D.. (2022). Statistical Inference on 2-Component Mixture of Topp-Leone Distribution, Bayesian and non-Bayesian Estimation. JOURNAL OF MATHEMATICAL EXTENSION, 16(9), 00-00. SID. https://sid.ir/paper/1066122/en

Vancouver: Copy

Kharazmi o., DEY S., KUMAR D.. Statistical Inference on 2-Component Mixture of Topp-Leone Distribution, Bayesian and non-Bayesian Estimation. JOURNAL OF MATHEMATICAL EXTENSION[Internet]. 2022;16(9):00-00. Available from: https://sid.ir/paper/1066122/en

IEEE: Copy

o. Kharazmi, S. DEY, and D. KUMAR, “Statistical Inference on 2-Component Mixture of Topp-Leone Distribution, Bayesian and non-Bayesian Estimation,” JOURNAL OF MATHEMATICAL EXTENSION, vol. 16, no. 9, pp. 00–00, 2022, [Online]. Available: https://sid.ir/paper/1066122/en

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