Estimation and prediction of modified progressive hybrid censored data from inverted exponentiated Rayleigh distribution

References

• Ahmed, N., Ali, S., & Shah, I. (2022). Type-I censored data monitoring using different conditional statistics. Quality and Reliability Engineering International, 38(1), 64–88. https://doi.org/10.1002/qre.2958
   Web of Science ®Google Scholar
• Bagheri, S. F., Asgharzadeh Fernandez, A. J., & Perez-Gonzalez, C. J. (2022). Joint prediction for future failures times under Type-II censoring. IEEE Transactions on Reliability, 71(1), 100–110. https://doi.org/10.1109/TR.2021.3068080
   Web of Science ®Google Scholar
• Balakrishnan, N., & Aggarwala, R. (2000). Progressive Censoring: Theory, Methods and Applications. Berkhauser. https://doi.org/10.1007/978-1-4612-1334-5
   Google Scholar
• Balakrishnan, N., Hayter, A. J., Liu, W., & Kiatsupaibul, S. (2015). Confidence intervals for quantiles of a two-parameter exponential distribution under progressive Type-II censoring. Communications in Statistics-Theory and Methods, 44(14), 3001–3010. https://doi.org/10.1080/03610926.2013.813051
   Web of Science ®Google Scholar
• Barndorff-Nielsen, O. E., & Cox, d. R. (1994). Inference and Asymptotic. Chapman & Hall. https://doi.org/10.1007/978-1-4899-3210-5
   Google Scholar
• Childs, A., Chandrasekar, B., Balakrishnan, N., & Kundu, d. (2003). Exact likelihood inference based on Type-I and Type-II hybrid censored samples from the exponential distribution. Annals of the Institute of Statistical Mathematics, 55(2), 319–330. https://doi.org/10.1007/BF02530502
   Web of Science ®Google Scholar
• Cho, Y., Sun, H., & Lee, K. (2015). Exact likelihood inference for an exponential parameter under generalized progressive hybrid censoring scheme. Statistical Methodology, 23, 18–34. https://doi.org/10.1016/j.stamet.2014.09.002
   Google Scholar
• El-Raheem, A. M. A. (2020). Optimal design of multiple accelerated life testing for generalized half-normal distribution under Type-I censoring. Journal of Computational and Applied Mathematics, 368, 112539. https://doi.org/10.1016/j.cam.2019.112539
   Web of Science ®Google Scholar
• El-Sagheer, R. M., Mahmoud, M. A. W., & Abdallah, S. H. M. (2018). Statistical inferences for new Weibull-Pareto distribution under an adaptive Type-II progressive censored data. Journal of Statistics and Management Systems, 21(6), 1021–1057. https://doi.org/10.1080/09720510.2018.1467628
   Web of Science ®Google Scholar
• Epstein, B. (1954). Truncated life tests in the exponential case. Annals of Mathematical Statistics, 25(3), 555–564. https://doi.org/10.1214/aoms/1177728723
   Google Scholar
• Fern´andez, F. E. (2007). On calculating generalized confidence intervals for the twoparameter exponential reliability function. Statistics, 41(2), 129–135. https://doi.org/10.1080/10485250601033172
   Web of Science ®Google Scholar
• Ghitany, M. E., Tuan, V. K., & Balakrishnan, N. (2014). Likelihood estimation for a general class of inverse exponentiated distributions based on complete and progressively censored data. Journal of Statistical Computation and Simulation, 84, 96–106. https://doi.org/10.1080/00949655.2012.696117
   Web of Science ®Google Scholar
• Grubbs, F. E. (1971). Approximate fiducial bounds on reliability for the two parameter negative exponential distribution. Technometrics, 13(4), 873–876. https://doi.org/10.1080/00401706.1971.10488858
   Web of Science ®Google Scholar
• Kayal, T., Tripathi, Y. M., & Rastogi, M. K. (2018). Estimation and prediction for an inverted exponentiated Rayleigh distribution under hybrid censoring. Communications in Statistics-Theory and Methods, 47(7), 1615–1640. https://doi.org/10.1080/03610926.2017.1322702
   Web of Science ®Google Scholar
• Kohansal, A., & Shoaee, S. (2021). Bayesian and classical estimation of reliability in a multicomponent stress-strength model under adaptive hybrid progressive censored data. Statistical Papers, 62(1), 309–359. https://doi.org/10.1007/s00362-019-01094-y
   Web of Science ®Google Scholar
• Koley, A., & Kundu, d. (2017). On generalized progressive hybrid censoring in presence of competing risks. Metrika, 80(4), 401–426. https://doi.org/10.1007/s00184-017-0611-6
   Web of Science ®Google Scholar
• Kundu, d., & Howlader, H. (2010). Bayesian inference and prediction of the inverse Weibull distribution for Type-II censored data. Computational Statistics & Data Analysis, 54(6), 1547–1558. https://doi.org/10.1016/j.csda.2010.01.003
   Web of Science ®Google Scholar
• Kundu, d., & Joarder, A. (2006). Analysis of Type-II progressively hybrid censored data. Computational Statistics & Data Analysis, 50(10), 2509–2528. 25. https://doi.org/10.1016/j.csda.2005.05.002
   Web of Science ®Google Scholar
• Lawless, J. F. (2003). Statistical models and methods for lifetime data, 2ed. Wiley. https://doi.org/10.1002/9781118033005
   Google Scholar
• Liu, S., & Gui, W. (2020). Estimating the Parameters of the Two-Parameter Rayleigh Distribution Based on Adaptive Type-II Progressive Hybrid Censored Data with Competing Risks. Mathematics, 8(10), 1783. https://doi.org/10.3390/math8101783
   Web of Science ®Google Scholar
• Mahto, A. K., Lodhi, C., Tripathi, Y. M., & Wang, L. (2022). On partially observed competing risk model under generalized progressive hybrid censoring for Lomax distribution. Quality Technology & Quantitative Management, 19(5), 562–586. https://doi.org/10.1080/16843703.2022.2049507
   Web of Science ®Google Scholar
• Mahto, A. K., Tripathi, Y. M., & Wu, S.-J. (2021). Statistical inference based on progressively type-II censored data from the Burr X distribution under progressive-stress accelerated life test. Journal of Statistical Computation and Simulation, 91(2), 368–382. https://doi.org/10.1080/00949655.2020.1815021
   Web of Science ®Google Scholar
• Maurya, R. K., Tripathi, Y. M., Sen, T., & Rastogi, M. K. (2019). On progressively censored inverted exponentiated Rayleigh distribution. Journal of Statistical Computation and Simulation, 89(3), 492–518. https://doi.org/10.1080/00949655.2018.1558225
   Web of Science ®Google Scholar
• Ma, J., Wang, L., Tripathi, Y. M., & Rastogi, M. K. (2021). Reliability inference for stressstrength model based on inverted exponential Rayleigh distribution under progressive Type-II censored data. Communications in Statistics-Simulation and Computation, 1-25. https://doi.org/10.1080/03610918.2021.1908552. 1–25.
   Web of Science ®Google Scholar
• Meeker, W. Q., Escobar, L. A., & Hong, Y. (2009). Using accelerated life tests results to predict product field reliability. Technometrics, 51(2), 146–161. https://doi.org/10.1198/TECH.2009.0016
   Web of Science ®Google Scholar
• Panahi, H., & Moradi, N. (2020). Estimation of the inverted exponentiated Rayleigh distribution based on adaptive Type-II progressive hybrid censored sample. Journal of Computational and Applied Mathematics, 364, 112345. https://doi.org/10.1016/j.cam.2019.112345
   Web of Science ®Google Scholar
• Qin, S., Wang, B. X., Wu, W., & Ma, C. (2022). The prediction intervals of remaining useful life based on constant stress accelerated life test data. European Journal of Operational Research, 301(2), 747–755. https://doi.org/10.1016/j.ejor.2021.11.026
   Web of Science ®Google Scholar
• Seo, J. I., & Kim, Y. (2017). Robust Bayesian estimation of a two-parameter exponential distribution under generalized Type-I progressive hybrid censoring. Communications in Statistics-Simulation and Computation, 46(7), 5795–5807. https://doi.org/10.1080/03610918.2016.1183779
   Web of Science ®Google Scholar
• Sharma, V. K., & Dey, S. (2019). Estimation of reliability of multicomponent stressstrength inverted exponentiated Rayleigh model. Journal of Industrial and Production Engineering, 36(3), 181–192. https://doi.org/10.1080/21681015.2019.1646032
   Web of Science ®Google Scholar
• Singh, S., Tripathi, Y. M., & Wu, S.-J. (2017). Bayesian estimation and prediction based on log-normal record values. Journal of Applied Statistics, 44(5), 916–940. https://doi.org/10.1080/02664763.2016.1189520
   Web of Science ®Google Scholar
• Stephens, M. A. (1986). Tests for the Exponential distribution. In R. B. D’Agostino & M. A. Stephens, Eds. Goodness-of-Fit Techniques. Marcel Dekker (pp. 421–459). https://doi.org/10.1201/9780203753064-10
   Google Scholar
• Valiollahi, R., Asgharzadeh, A., & Kundu, d. (2017). Prediction of future failures for generalized exponential distribution under Type-I or Type-II hybrid censoring. Brazilian Journal of Probability and Statistics, 31(1), 41–61. https://doi.org/10.1214/15-BJPS302
   Web of Science ®Google Scholar
• Viveros, R., & Balakrishnan, N. (1994). Interval estimation of parameters of life from progressively censored data. Technometrics, 36(1), 84–91. https://doi.org/10.1080/00401706.1994.10485403
   Web of Science ®Google Scholar
• Volovskiy, G., & Kamps, U. (2020). Maximum observed likelihood prediction of future record values. TEST, 29(4), 1072–1097. https://doi.org/10.1007/s11749-020-00701-7
   Web of Science ®Google Scholar
• Wang, L., Tripathi, Y. M., Lodhi, C., & Zuo, X. (2022). Inference for constant-stress Weibull competing risks model under generalized progressive hybrid censoring. Mathematics and Computers in Simulation, 192, 70–83. https://doi.org/10.1016/j.matcom.2021.08.017
   Web of Science ®Google Scholar
• Weerahandi, S. (2004). Generalized inference in repeated measures: Exact methods in MANOVA and mixed models. Wiley.
   Google Scholar
• Xu, X., Tang, S., Yu, C., Xie, J., & Ouyang, M. (2021). Remaining useful life prediction of lithium-ion batteries based on Wiener process under time-varying temperature condition. Reliability Engineering & System Safety, 214(9), 107675. https://doi.org/10.1016/j.ress.2021.107675
   Google Scholar
• Zhang, Z., Si, X., Hu, C., & Lei, Y. (2018). Degradation data analysis and remaining useful life estimation: A review on Wiener-process-based methods. European Journal of Operational Research, 271(3), 775–796. https://doi.org/10.1016/j.ejor.2018.02.033
   Web of Science ®Google Scholar
• Zhu, T. (2021). A new approach for estimating parameters of two-parameter bathtubshaped lifetime distribution under modified progressive hybrid censoring. Quality and Reliability Engineering International, 37(5), 2288–2304. https://doi.org/10.1002/qre.2858
   Web of Science ®Google Scholar