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The Half-Logistic Generalized Weibull Distribution

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  • Masood Anwar
  • Amna Bibi

Abstract

A new three-parameter generalized distribution, namely, half-logistic generalized Weibull (HLGW) distribution, is proposed. The proposed distribution exhibits increasing, decreasing, bathtub-shaped, unimodal, and decreasing-increasing-decreasing hazard rates. The distribution is a compound distribution of type I half-logistic-G and Dimitrakopoulou distribution. The new model includes half-logistic Weibull distribution, half-logistic exponential distribution, and half-logistic Nadarajah-Haghighi distribution as submodels. Some distributional properties of the new model are investigated which include the density function shapes and the failure rate function, raw moments, moment generating function, order statistics, L-moments, and quantile function. The parameters involved in the model are estimated using the method of maximum likelihood estimation. The asymptotic distribution of the estimators is also investigated via Fisher’s information matrix. The likelihood ratio (LR) test is used to compare the HLGW distribution with its submodels. Some applications of the proposed distribution using real data sets are included to examine the usefulness of the distribution.

Suggested Citation

  • Masood Anwar & Amna Bibi, 2018. "The Half-Logistic Generalized Weibull Distribution," Journal of Probability and Statistics, Hindawi, vol. 2018, pages 1-12, January.
    • Handle: RePEc:hin:jnljps:8767826
    DOI: 10.1155/2018/8767826
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    Cited by:

    1. Ramadan A. ZeinEldin & Christophe Chesneau & Farrukh Jamal & Mohammed Elgarhy, 2019. "Statistical Properties and Different Methods of Estimation for Type I Half Logistic Inverted Kumaraswamy Distribution," Mathematics, MDPI, vol. 7(10), pages 1-24, October.
    2. Ammara Tanveer & Muhammad Azam & Muhammad Aslam & Muhammad Shujaat Navaz, 2020. "Attribute np control charts using resampling systems for monitoring non-conforming items under exponentiated half-logistic distribution," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 30(2), pages 115-143.
    3. Mohamed S. Eliwa & Muhammad H. Tahir & Muhammad A. Hussain & Bader Almohaimeed & Afrah Al-Bossly & Mahmoud El-Morshedy, 2023. "Univariate Probability-G Classes for Scattered Samples under Different Forms of Hazard: Continuous and Discrete Version with Their Inferences Tests," Mathematics, MDPI, vol. 11(13), pages 1-24, June.

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