Open Access
Issue
JNWPU
Volume 42, Number 3, June 2024
Page(s) 487 - 497
DOI https://doi.org/10.1051/jnwpu/20244230487
Published online 01 October 2024
  1. MAO Shisong. Analysis of constant stress AFT for Weibull distribution[J]. Chinese Journal of Qualty and Reliabicity, 2003, 6: 16–23 [Google Scholar]
  2. VOICULESCU S, GUERIN F, BARREAU M, et al. Bayesian estimation in accelerated life testing application on exponential-arrhenius model[J]. International Journal of Product Development, 2009, 7(3/4): 246–260. [Article] [CrossRef] [Google Scholar]
  3. MA Jiming, RUAN Lingyan, FU Yongling, et al. Current status of accelerated life testing for aviation hydraulic pumps[J].Chinese Hydraulics & Pneumatics, 2015(6): 6–12. [Article] (in Chinese) [Google Scholar]
  4. ZHANG Chunhua, CHEN Xun, WEN Xisen. Step-down-stress accelerated life testing——methodology[J]. Acta Armamentarii, 2005(5): 661–665. [Article] (in Chinese) [Google Scholar]
  5. ZHANG Chunhua, CHEN Xun, WEN Xisen. Step-down-stress accelerated life testing——statistical analysis[J]. Acta Armamentarii, 2005(5): 666–669. [Article] (in Chinese) [Google Scholar]
  6. SUN Tianyu, SHI Yimin, XIE Qi. Analysis of reliability performances on two alternative step-stress accelerated life test for Weibull distribution[J]. Journal of Mechanical Strength, 2013, 35(3): 253–257. [Article] [Google Scholar]
  7. KOU Haixia, AN Zongwen, LIU Bo. Double synchronous-step-down-stress accelerated life testing method[J]. Journal of University of Electronic Science and Technology of China, 2016, 45(2): 316–320. [Article] (in Chinese) [Google Scholar]
  8. CHEN Juan, LI Jia, Wang Deyi, et al. Double crossed step-down-stress accelerated life testing for pneumatic cylinder based on cumulative damage model[J]. Advanced Materials Research, 2014, 871: 56–63 [Google Scholar]
  9. HAN D, BALAKRISHNAN N. Inference for a simple step-stress model with competing risks for failure from the exponential distribution under time constraint[J]. Computational Statistics & Data Analysis, 2010, 54(9): 2066–2081 [CrossRef] [Google Scholar]
  10. ZHANG Chunfang, SHI Yimin, WU Min. Statistical inference on competing risks model from exponentiated Weibull distribution under type-Ⅰ progressive hybrid censoring data[J]. Chinese Journal of Applied Probability and Statistics, 2018, 34(4): 331–344. [Article] (in Chinese) [Google Scholar]
  11. ALAM I, ANWAR S, SHARMA L K, et al. Competing risk analysis in constant stress partially accelerated life tests under censored information[J]. Annals of Data Science, 2023, 10(5): 1379–1403. [Article] [CrossRef] [Google Scholar]
  12. PAREEK B, KUNDU D, KUMAR S. On progressively censored competing risks data for Weibull distributions[J]. Computational Statistics & Data Analysis, 2009, 53(12): 4083–4094 [CrossRef] [Google Scholar]
  13. HUANG Wenping, ZHOU Jinglun, NING Juhong, et al. Parameter estimation of Lindley distribution with competing risk data[J]. Systems Engineering and Electronics, 2016, 38(2): 464–469. [Article] (in Chinese) [Google Scholar]
  14. WANG Liang. Inference of progressively censored competing risks data from Kumaraswamy distributions[J]. Journal of Computational And Applied Mathematics, 2018, 343: 719–736. [Article] [Google Scholar]
  15. EPSTEIN B. Truncated life tests in the exponential case[J]. The Annals of Mathematical Statistics, 1954, 25: 555–564. [Article] [CrossRef] [Google Scholar]
  16. KUNDU D, JOARDER A. Analysis of type-Ⅱ progressively hybrid censored data[J]. Computational Statistics & Data Analysis, 2006, 50 [Google Scholar]
  17. NG H, KUNDU D, PING S C Statistical analysis of exponential lifetimes under an adaptive type-Ⅱ progressive censoring scheme[J]. Naval Research Logistics, 2010, 56(8): 687–698 [Google Scholar]
  18. MAHMOUD A W M, SOLIMAN A A, ABD ELLAH A, et al. Estimation of generalized pareto under an adaptive type-Ⅱ progressive censoring[J]. Intelligent Information Management, 2013, 5: 73–83. [Article] [CrossRef] [Google Scholar]
  19. MOHIEELDIN M M M, AMEIN M, SHAFAY A R, et al. Estimation of generalized exponential distribution based on anadaptive progressively type-Ⅱ censored sample[J]. Journal of Statistical Computatian and Simulation, 2017, 87: 1292–1304. [Article] [CrossRef] [Google Scholar]
  20. NASSAR M, ABO-KASEM O E, ZHANG C, et al. Analysis of weibull distribution under adaptive type-Ⅱ progressive hybrid censoring scheme[J]. Journal of the Indian Society for Probability and Statistics, 2018(2): 1–41 [Google Scholar]
  21. REN Junru, GUI Wenhao. Statistical analysis of adaptive type-Ⅱ progressively censored competing risks for weibull models[J]. Applied Mathematical Modelling, 2021, 98: 323–342. [Article] [CrossRef] [Google Scholar]
  22. WU Min, SHI Yiming, SUN Yudong. Inference for accelerated competing failure models from Weibull distribution under type-Ⅰ progressive hybrid censoring[J]. Journal of Computational & Applied Mathematics, 2014, 263: 423–431 [Google Scholar]
  23. CHEN Minghui, SHAO Qiman. Monte Carlo estimation of Bayesian credible and HPD intervals[J]. Journal of Computational & Graphical Statistics, 1999, 8(1): 69–92 [Google Scholar]
  24. BALAKRISHNAN N, SANDU R A. A simple simulation algorithm for generating progressive type-Ⅱ censored samples[J]. The American Stueistician, 1995, 49: 229–230. [Article] [CrossRef] [Google Scholar]

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