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The logistic Nadarajah–Haghighi distribution and its associated regression model for reliability applications

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  • Peña-Ramírez, Fernando A.
  • Guerra, Renata Rojas
  • Canterle, Diego Ramos
  • Cordeiro, Gauss M.

Abstract

We introduce a new three-parameter model called the logistic Nadarajah–Haghighi distribution. An important property of the proposed distribution is that it can produce decreasing and unimodal failure rates. These behaviors can arise in several reliability problems. We provide some useful quantile measures and other reliability properties. We present the maximum likelihood estimators of the model parameters. We perform applications that show the usefulness of the new distribution for modeling mechanical components failure times and impact factors in the informetrics literature. Further, we present a parametric regression model for right-censored data considering a median-based parametrization of the new distribution. A Monte Carlo study is carried out to evaluate the performance of the estimators. Finally, we analyze the reliability of pressure vessels wrapped with a Kevlar fibre using the proposed regression model.

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  • Peña-Ramírez, Fernando A. & Guerra, Renata Rojas & Canterle, Diego Ramos & Cordeiro, Gauss M., 2020. "The logistic Nadarajah–Haghighi distribution and its associated regression model for reliability applications," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    • Handle: RePEc:eee:reensy:v:204:y:2020:i:c:s0951832020306979
    DOI: 10.1016/j.ress.2020.107196
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    as
    1. Lu, Yaohui & Zheng, Heyan & Zeng, Jing & Chen, Tianli & Wu, Pingbo, 2019. "Fatigue life reliability evaluation in a high-speed train bogie frame using accelerated life and numerical test," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 221-232.
    2. Bebbington, Mark & Lai, Chin-Diew & Zitikis, RiÄ ardas, 2007. "A flexible Weibull extension," Reliability Engineering and System Safety, Elsevier, vol. 92(6), pages 719-726.
    3. Lemonte, Artur J., 2013. "A new exponential-type distribution with constant, decreasing, increasing, upside-down bathtub and bathtub-shaped failure rate function," Computational Statistics & Data Analysis, Elsevier, vol. 62(C), pages 149-170.
    4. Jin, Guang & Matthews, David E. & Zhou, Zhongbao, 2013. "A Bayesian framework for on-line degradation assessment and residual life prediction of secondary batteries inspacecraft," Reliability Engineering and System Safety, Elsevier, vol. 113(C), pages 7-20.
    5. Wang, Xiaolin & Balakrishnan, Narayanaswamy & Guo, Bo, 2014. "Residual life estimation based on a generalized Wiener degradation process," Reliability Engineering and System Safety, Elsevier, vol. 124(C), pages 13-23.
    6. Wang, Hongzhou, 2002. "A survey of maintenance policies of deteriorating systems," European Journal of Operational Research, Elsevier, vol. 139(3), pages 469-489, June.
    7. Ahmad, Abd EL-Baset A. & Ghazal, M.G.M., 2020. "Exponentiated additive Weibull distribution," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    8. Dong, Y. & Teixeira, A.P. & Guedes Soares, C., 2020. "Application of adaptive surrogate models in time-variant fatigue reliability assessment of welded joints with surface cracks," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    9. Haghighi, Firoozeh, 2014. "Optimal design of accelerated life tests for an extension of the exponential distribution," Reliability Engineering and System Safety, Elsevier, vol. 131(C), pages 251-256.
    10. Prataviera, Fábio & Ortega, Edwin M.M. & Cordeiro, Gauss M. & Pescim, Rodrigo R. & Verssani, Bruna A.W., 2018. "A new generalized odd log-logistic flexible Weibull regression model with applications in repairable systems," Reliability Engineering and System Safety, Elsevier, vol. 176(C), pages 13-26.
    11. Li, Mingyang & Meng, Hongdao & Zhang, Qingpeng, 2017. "A nonparametric Bayesian modeling approach for heterogeneous lifetime data with covariates," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 95-104.
    12. Shakhatreh, Mohammed K. & Lemonte, Artur J. & Moreno–Arenas, Germán, 2019. "The log-normal modified Weibull distribution and its reliability implications," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 6-22.
    13. Chang, Dong Shang, 2000. "Optimal burn-in decision for products with an unimodal failure rate function," European Journal of Operational Research, Elsevier, vol. 126(3), pages 534-540, November.
    14. N. Balakrishnan & Debasis Kundu, 2019. "Birnbaum‐Saunders distribution: A review of models, analysis, and applications," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 35(1), pages 4-49, January.
    15. Xu, Meng & Droguett, Enrique López & Lins, Isis Didier & das Chagas Moura, Márcio, 2017. "On the q-Weibull distribution for reliability applications: An adaptive hybrid artificial bee colony algorithm for parameter estimation," Reliability Engineering and System Safety, Elsevier, vol. 158(C), pages 93-105.
    16. Baker, Rose, 2019. "New survival distributions that quantify the gain from eliminating flawed components," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 493-501.
    17. Zhao, Yan-Gang & Zhang, Xuan-Yi & Lu, Zhao-Hui, 2018. "A flexible distribution and its application in reliability engineering," Reliability Engineering and System Safety, Elsevier, vol. 176(C), pages 1-12.
    18. M. H. Tahir & Gauss M. Cordeiro & Ayman Alzaatreh & M. Mansoor & M. Zubair, 2016. "The logistic-X family of distributions and its applications," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 45(24), pages 7326-7349, December.
    19. Raffaele Argiento & Alessandra Guglielmi & Jacopo Soriano, 2013. "A semiparametric Bayesian generalized linear mixed model for the reliability of Kevlar fibers," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 29(5), pages 410-423, September.
    20. Tavangar, Mahdi & Bairamov, Ismihan, 2015. "On conditional residual lifetime and conditional inactivity time of k-out-of-n systems," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 225-233.
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