Statistical inference of dependent competing risks from Marshall–Olkin bivariate Burr-XII distribution under complex censoring

References

• Ahmed, E. A., Z. A. Alhussain, M. M. Salah, H. H. Ahmed, and M. S. Eliwa. 2020. Inference of progressively type-II censored competing risks data from Chen distribution with an application. Journal of Applied Statistics 47 (13-15):2492–524.
   PubMed Web of Science ®Google Scholar
• Asadi, M., and Y. Zohrevand. 2007. On the dynamic cumulative residual entropy. Journal of Statistical Planning and Inference 137 (6):1931–41. doi:10.1016/j.jspi.2006.06.035.
   Web of Science ®Google Scholar
• Balakrishnan, N., and R. A. Sandhu. 1995. A simple simulational algorithm for generating progressive type-II censored samples. The American Statistician 49 (2):229–30.
   Web of Science ®Google Scholar
• Balakrishnan, N, and E. Cramer. 2014. The art of progressive censoring: Applications to reliability and quality. New York: Springer.
   Google Scholar
• Burr, I. W. 1942. Cumulative frequency functions. The Annals of Mathematical Statistics 13 (2):215–32. doi:10.1214/aoms/1177731607.
   Google Scholar
• Dimitrova, D. S., S. Haberman, and V. K. Kaishev. 2013. Dependent competing risks: Cause elimination and its impact on survival. Insurance: Mathematics and Economics 53 (2):464–77. doi:10.1016/j.insmatheco.2013.07.008.
   Web of Science ®Google Scholar
• Feizjavadian, S., and R. Hashemi. 2015. Analysis of dependent competing risks in the presence of progressive hybrid censoring using Marshall–Olkin bivariate Weibull distribution. Computational Statistics & Data Analysis 82:19–34.
   Web of Science ®Google Scholar
• Hakim, A. R., I. Fithriani, and M. Novita. 2021. Properties of burr distribution and its application to heavy-tailed survival time data. Journal of Physics: Conference Series 1725:012016.
   Google Scholar
• Han, D., and N. Balakrishnan. 2010. Inference for a simple step-stress model with competing risks for failure from the exponential distribution under time constraint. Computational Statistics & Data Analysis 54 (9):2066–81.
   Web of Science ®Google Scholar
• Hasan, H., H. Muhammed, and O. Abuelamayem. 2020. Estimation of the bivariate Kumaraswamy lifetime distribution under progressive type-I censoring. Journal of Data Science 18 (4):739–49.
   Google Scholar
• Kohansal, A., and S. Shoaee. 2021. Bayesian and classical estimation of reliability in a multicomponent stress-strength model under adaptive hybrid progressive censored data. Statistical Papers 62:309–59.
   Web of Science ®Google Scholar
• Kumar, D. 2017. The Burr type XII distribution with some statistical properties. Journal of Data Science 15:509–34.
   Google Scholar
• Kundu, D., and A. K. Gupta. 2013. Bayes estimation for the Marshall–Olkin bivariate Weibull distribution. Computational Statistics & Data Analysis 57 (1):271–81.
   Web of Science ®Google Scholar
• Marshall, A. W., and I. Olkin. 1967. A multivariate exponential distribution. Journal of the American Statistical Association 62 (317):30–44. doi:10.1080/01621459.1967.10482885.
   Web of Science ®Google Scholar
• Meeker, W. Q, and L. Escobar. 1998. Statistical methods for reliability data. New York: Wiley.
   Google Scholar
• Ng, H. K. T., D. Kundu, and P. Chan. 2009. Statistical analysis of exponential lifetimes under an adaptive type-II progressive censoring scheme. Naval Research Logistics (NRL) 56:687–98.
   Web of Science ®Google Scholar
• Peña, E. A., and A. K. Gupta. 1990. Bayes estimation for the Marshall–Olkin exponential distribution. Journal of the Royal Statistical Society: Series B (Methodological) 52 (2):379–89.
   Google Scholar
• Rajesh, G., E. Abdul-Sathar, K. Muraleedharan Nair, and K. Reshmi. 2014. Bivariate extension of dynamic cumulative residual entropy. Statistical Methodology 16:72–82. doi:10.1016/j.stamet.2013.07.006.
   Web of Science ®Google Scholar
• Rao, M., Y. Chen, B. Vemuri, and F. Wang. 2004. Cumulative residual entropy: A new measure of information. IEEE Transactions on Information Theory 50 (6):1220–8. doi:10.1109/TIT.2004.828057.
   Web of Science ®Google Scholar
• Ren, J., and W. Gui. 2021. Inference and optimal censoring scheme for progressively type-II censored competing risks model for generalized Rayleigh distribution. Computational Statistics 36:479–513.
   Web of Science ®Google Scholar
• Salemi, U. H., S. Rezaei, and S. Nadarajah. 2019. A-optimal and D-optimal censoring plans in progressively type-II right censored order statistics. Statistical Papers 60:1349–67.
   Web of Science ®Google Scholar
• Samanta, D., and D. Kundu. 2021. Bayesian inference of a dependent competing risk data. Journal of Statistical Computation and Simulation 91 (15): 3069–86. doi:10.1080/00949655.2021.1917575.
   Web of Science ®Google Scholar
• Shi, Y., and M. Wu. 2016. Statistical analysis of dependent competing risks model from gompertz distribution under progressively hybrid censoring. Springerplus 5 (1):1745.
   PubMedGoogle Scholar
• Soliman, A., E. Ahmed, A. A. Farghal, and A. Al-Shibany. 2020. Estimation of generalized inverted exponential distribution based on adaptive type-II progressive censoring data. Journal of Statistics Applications & Probability 9 (2):215–30.
   Google Scholar
• Tian, Y., and W. Gui. 2021. Inference of weighted exponential distribution under progressively type-II censored competing risks model with electrodes data. Journal of Statistical Computation and Simulation 91 (16): 3426–52. doi:10.1080/00949655.2021.1928128.
   Web of Science ®Google Scholar
• Wang, B. X., K. Yu, and Z. Sheng. 2014. New inference for constant-stress accelerated life tests with Weibull distribution and progressively type-II censoring. IEEE Transactions on Reliability 63 (3):807–15.
   Web of Science ®Google Scholar
• Wang, L., M. Li, and Y. M. Tripathi. 2020. Inference for dependent competing risks from bivariate Kumaraswamy distribution under generalized progressive hybrid censoring. Communications in Statistics - Simulation and Computation 51 (6): 3100–23. doi:10.1080/03610918.2019.1708929.
   Web of Science ®Google Scholar
• Wang, L., Y. M. Tripathi, S. Dey, and Y. Shi. 2021. Inference for dependence competing risks with partially observed failure causes from bivariate Gompertz distribution under generalized progressive hybrid censoring. Quality and Reliability Engineering International 37 (3):1150–72.
   Web of Science ®Google Scholar
• Wu, M., Y. Shi, and Y. Sun. 2014. Inference for accelerated competing failure models from Weibull distribution under type-I progressive hybrid censoring. Journal of Computational and Applied Mathematics 263:423–31.
   Web of Science ®Google Scholar
• Yang, A., E. Li, M. Tian, and Y. Tian. 2016. Parameters estimation for mixed generalized inverted exponential distributions with type-II progressive hybrid censoring. Hacettepe Journal of Mathematics and Statistics 47 (4):1023–39.
   Web of Science ®Google Scholar
• Ye, Z.-S., P.-S. Chan, M. Xie, and H. K. T. Ng. 2014. Statistical inference for the extreme value distribution under adaptive type-II progressive censoring schemes. Journal of Statistical Computation and Simulation 84 (5):1099–114.
   Web of Science ®Google Scholar
• Zhang, C., Y. Shi, and M. Wu. 2016. Statistical inference for competing risks model in step-stress partially accelerated life tests with progressively type-I hybrid censored Weibull life data. Journal of Computational and Applied Mathematics 297:65–74.
   Web of Science ®Google Scholar
• Zimmer, W. J., J. B. Keats, and F. K. Wang. 1998. The Burr XII distribution in reliability analysis. Journal of Quality Technology 30 (4):386–94. doi:10.1080/00224065.1998.11979874.
   Web of Science ®Google Scholar