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Modifications of the Weibull distribution: A review

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Cited by:

  1. Abdoulaye Diamoutene & Farid Noureddine & Rachid Noureddine & Bernard Kamsu-Foguem & Diakarya Barro, 2020. "Proportional hazard model for cutting tool recovery in machining," Journal of Risk and Reliability, , vol. 234(2), pages 322-332, April.
  2. Freddy Hernández & Viviana Giampaoli, 2018. "The Impact of Misspecified Random Effect Distribution in a Weibull Regression Mixed Model," Stats, MDPI, vol. 1(1), pages 1-29, May.
  3. Nagode, Marko & Oman, Simon & Klemenc, Jernej & Panić, Branislav, 2023. "Gumbel mixture modelling for multiple failure data," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
  4. Xiang Jia & Saralees Nadarajah & Bo Guo, 2020. "Inference on q-Weibull parameters," Statistical Papers, Springer, vol. 61(2), pages 575-593, April.
  5. 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.
  6. Sulewski Piotr & Szymkowiak Magdalena, 2022. "The Weibull lifetime model with randomised failure-free time," Statistics in Transition New Series, Polish Statistical Association, vol. 23(4), pages 59-76, December.
  7. Gauss M. Cordeiro & Elisângela C. Biazatti & Luís H. de Santana, 2023. "A New Extended Weibull Distribution with Application to Influenza and Hepatitis Data," Stats, MDPI, vol. 6(2), pages 1-17, May.
  8. Shuto, Susumu & Amemiya, Takashi, 2022. "Sequential Bayesian inference for Weibull distribution parameters with initial hyperparameter optimization for system reliability estimation," Reliability Engineering and System Safety, Elsevier, vol. 224(C).
  9. Jia, Xiang & Guo, Bo, 2022. "Reliability analysis for complex system with multi-source data integration and multi-level data transmission," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
  10. Achim Kampker & Heiner Hans Heimes & Christian Offermanns & Merlin Frank & Domenic Klohs & Khanh Nguyen, 2023. "Prediction of Battery Return Volumes for 3R: Remanufacturing, Reuse, and Recycling," Energies, MDPI, vol. 16(19), pages 1-22, September.
  11. Szymkowiak, Magdalena & Iwińska, Maria, 2016. "Characterizations of Discrete Weibull related distributions," Statistics & Probability Letters, Elsevier, vol. 111(C), pages 41-48.
  12. Khayyam, Hamid & Naebe, Minoo & Bab-Hadiashar, Alireza & Jamshidi, Farshid & Li, Quanxiang & Atkiss, Stephen & Buckmaster, Derek & Fox, Bronwyn, 2015. "Stochastic optimization models for energy management in carbonization process of carbon fiber production," Applied Energy, Elsevier, vol. 158(C), pages 643-655.
  13. Zeng, Hongtao & Lan, Tian & Chen, Qiming, 2016. "Five and four-parameter lifetime distributions for bathtub-shaped failure rate using Perks mortality equation," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 307-315.
  14. Negreiros, Ana Cláudia Souza Vidal de & Lins, Isis Didier & Moura, Márcio José das Chagas & Droguett, Enrique López, 2020. "Reliability data analysis of systems in the wear-out phase using a (corrected) q-Exponential likelihood," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
  15. Musleh, Rola M. & Helu, Amal, 2014. "Estimation of the inverse Weibull distribution based on progressively censored data: Comparative study," Reliability Engineering and System Safety, Elsevier, vol. 131(C), pages 216-227.
  16. Yolanda M. Gómez & Diego I. Gallardo & Carolina Marchant & Luis Sánchez & Marcelo Bourguignon, 2023. "An In-Depth Review of the Weibull Model with a Focus on Various Parameterizations," Mathematics, MDPI, vol. 12(1), pages 1-19, December.
  17. Jia, Xiang & Wang, Dong & Jiang, Ping & Guo, Bo, 2016. "Inference on the reliability of Weibull distribution with multiply Type-I censored data," Reliability Engineering and System Safety, Elsevier, vol. 150(C), pages 171-181.
  18. He, Bo & Cui, Weimin & Du, Xiaofeng, 2016. "An additive modified Weibull distribution," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 28-37.
  19. 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.
  20. Bentaha, Mohand-Lounes & Voisin, Alexandre & Marangé, Pascale, 2020. "A decision tool for disassembly process planning under end-of-life product quality," International Journal of Production Economics, Elsevier, vol. 219(C), pages 386-401.
  21. Örkcü, H. Hasan & Özsoy, Volkan Soner & Aksoy, Ertugrul & Dogan, Mustafa Isa, 2015. "Estimating the parameters of 3-p Weibull distribution using particle swarm optimization: A comprehensive experimental comparison," Applied Mathematics and Computation, Elsevier, vol. 268(C), pages 201-226.
  22. Massimo Conti & Simone Orcioni, 2020. "Modeling of Failure Probability for Reliability and Component Reuse of Electric and Electronic Equipment," Energies, MDPI, vol. 13(11), pages 1-18, June.
  23. XiaoFei, Lu & Min, Liu, 2014. "Hazard rate function in dynamic environment," Reliability Engineering and System Safety, Elsevier, vol. 130(C), pages 50-60.
  24. Luis Carlos Méndez-González & Luis Alberto Rodríguez-Picón & Manuel Iván Rodríguez Borbón & Hansuk Sohn, 2023. "The Chen–Perks Distribution: Properties and Reliability Applications," Mathematics, MDPI, vol. 11(13), pages 1-19, July.
  25. Filippo Domma & Francesca Condino & Božidar V. Popović, 2017. "A new generalized weighted Weibull distribution with decreasing, increasing, upside-down bathtub, N-shape and M-shape hazard rate," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(16), pages 2978-2993, December.
  26. 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.
  27. Jia, Xiang & Cheng, Zhijun & Guo, Bo, 2022. "Reliability analysis for system by transmitting, pooling and integrating multi-source data," Reliability Engineering and System Safety, Elsevier, vol. 224(C).
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