Inference for partially observed competing risks model for Kumaraswamy distribution under generalized progressive hybrid censoring

References

• N. Balakrishnan and R. Aggarwala, Progressive Censoring: Theory, Methods, and Applications, Birkhauser, Boston, 2000.
   Google Scholar
• N. Balakrishnan and E. Cramer, The Art of Progressive Censoring, Springer, New York, 2014.
   Google Scholar
• Y. Cheng and J.P. Fine, Nonparametric estimation of cause-specific cross hazard ratio with bivariate competing risks data, Biometrika 95 (2008), pp. 233–240.
   Web of Science ®Google Scholar
• A. Childs, B. Chandrasekar, and N. Balakrishnan, Exact likelihood inference for an exponential parameter under progressive hybrid censoring schemes, in Statistical Models and Methods for Biomedical and Technical Systems, Birkhauser, Boston, 2008, pp. 319–330.
   Google Scholar
• A. Childs, B. Chandrasekar, and D. Kundu, Exact likelihood inference based on Type-I and Type-II hybrid censored samples from the exponential distribution. Ann. Inst. Stat. Math. 55 (2003), pp. 319–330.
   Web of Science ®Google Scholar
• Y. Cho, H. Sun, and K. Lee, Exact likelihood inference for an exponential parameter under generalized progressive hybrid censoring scheme. Stat. Methodol. 23 (2015), pp. 18–34.
   Google Scholar
• E. Cramer and AB. Schmiedt, Progressively Type-II censored competing risks data from Lomax distributions. Comput. Stat. Data Anal. 55 (2011), pp. 1285–1303.
   Web of Science ®Google Scholar
• M.J. Crowder, Classical Competing Risks, Chapman and Hall, Boca Raton, FL, 2001.
   Google Scholar
• S. Dey and T. Dey, On progressively censored generalized inverted exponential distribution. J. Appl. Stat. 41 (2014), pp. 2557–2576.
   Web of Science ®Google Scholar
• A. Ganguly, D. Kundu, and S. Mitra, Bayesian analysis of a simple step-stress model under Weibull lifetimes. IEEE Trans. Reliab. 64 (2014), pp. 473–485.
   Web of Science ®Google Scholar
• R. Gholizadeh, M. Khalilpor, and M. Hadian, Bayesian estimations in the Kumaraswamy distribution under progressively type II censoring data. Int. J. Eng. Sci. Tech. 3 (2011), pp. 47–65.
   Google Scholar
• M.C. Jones, Kumaraswamy's distribution: A beta-type distribution with some tractability advantages. Stat. Methodol. 6 (2009), pp. 70–81.
   Google Scholar
• A. Koley and D. Kundu, On generalized progressive hybrid censoring in presence of competing risks. Metrika 80 (2017), pp. 401–426.
   Web of Science ®Google Scholar
• D. Kundu and A. Joarder, Analysis of type-II progressively hybrid censored data. Comput. Stat. Data Anal. 50 (2006), pp. 2509–2528.
   Web of Science ®Google Scholar
• D. Kundu and B. Pradhan, Bayesian analysis of progressively censored competing risks data. Sankhya B 73 (2011), pp. 276–296.
   Google Scholar
• P. Kumaraswamy, A generalized probability density function for double-bounded random processes. J. Hydrol. 46 (1980), pp. 79–88.
   Web of Science ®Google Scholar
• D. Kundu, On hybrid censored weibull distribution. J. Stat. Plann. Inference 137 (2007), pp. 2127–2142.
   Web of Science ®Google Scholar
• C.T. Lin, C.C. Chou, and Y.L. Huang, Inference for the Weibull distribution with progressive hybrid censoring. Comput. Stat. Data Anal. 56 (2012), pp. 451–467.
   Web of Science ®Google Scholar
• C.T. Lin and Y.L. Huang, On progressive hybrid censored exponential distribution. J. Stat. Comput. Simul. 82 (2012), pp. 689–709.
   Web of Science ®Google Scholar
• C. Lodhi, Y.M. Tripathi, and M.K. Rastogi, Estimating the parameters of a truncated normal distribution under progressive type II censoring. Commun. Stat. Simul. Comput. (2019). doi:https://doi.org/10.1080/03610918.2019.1614619
   Google Scholar
• A.K. Mahto, S. Dey, and Y.M. Tripathi, Statistical inference on progressive-stress accelerated life testing for the logistic exponential distribution under progressive type-I censoring. Qual. Reliab. Eng. Int. 36 (2020), pp. 112–124.
   Web of Science ®Google Scholar
• R.K. Maurya, Y.M. Tripathi, and M.K. Rastogi, Parameter estimation for a Burr XII distribution under progressive censoring, Am. J. Math. Manage. Sci. 36 (2017), pp. 259–276.
   Google Scholar
• S.G. Meintanis, Test of fit for Marshall–Olkin distributions with applications, J. Stat. Plann. Inference 137 (2007), pp. 3954–3963.
   Web of Science ®Google Scholar
• S. Mondal and D. Kundu, Point and interval estimation of Weibull parameters based on joint progressively censored data, Sankhya B. 81 (2019), pp. 1–25.
   Google Scholar
• S. Mondal and D. Kundu, Bayesian inference for Weibull distribution under the balanced joint type-II progressive censoring scheme, Am. J. Math. Manage. Sci. 39 (2020), pp. 56–74.
   Google Scholar
• S. Nadarajah, On the distribution of kumaraswamy, J. Hydrol. (Amst). 348 (2008), pp. 568–569.
   Web of Science ®Google Scholar
• M. Nadar and F. Kizilaslan, Classical and Bayesian estimation of P(X<Y) using upper record values from Kumaraswamy distribution, Stat. Papers. 55 (2014), pp. 751–783.
   Web of Science ®Google Scholar
• M. Nadar, F. Kizilaslan, and A. Papadopoulos, Classical and Bayesian estimation of P(Y<X) for Kumaraswamy's distribution, J. Stat. Comput. Simul. 84 (2014), pp. 1505–1529.
   Web of Science ®Google Scholar
• W. Narendranathan and M.B. Stewart, Simple methods for testing for the proportionality of cause-specific hazards in competing risk models, Oxf. Bull. Econ. Stat. 53 (1991), pp. 331–340.
   Web of Science ®Google Scholar
• E.A. Pena and A.K. Gupta, Bayes estimation for the Marshall-Olkin exponential distribution, J. R. Stat. Soc. Ser. B. 52 (1990), pp. 379–389.
   Google Scholar
• M. Pintilie, Competing Risks: A Practical Perspective, Wiley, New York: 2006.
   Google Scholar
• B. Pradhan and D. Kundu, Inference and optimal censoring schemes for progressively censored Birnbaum–Saunders distribution, J. Stat. Plann. Inference 143 (2013), pp. 1098–1108.
   Web of Science ®Google Scholar
• M.K. Rastogi and Y.M. Tripathi, Inference on unknown parameters of a Burr distribution under hybrid censoring, Stat. Papers 54 (2013), pp. 619–643.
   Web of Science ®Google Scholar
• T. Sen, R. Bhattacharya, and Y.M. Tripathi, Inference and optimum life testing plans based on type-II progressive hybrid censored generalized exponential data, Commun. Stat. Simul. Comput. 49 (2019), pp. 3254–3282.
   Web of Science ®Google Scholar
• A. Sen, N. Kannan, and D. Kundu, Bayesian planning and inference of a progressively censored sample from linear hazard rate distribution, Comput. Stat. Data Anal. 62 (2013), pp. 108–121.
   Web of Science ®Google Scholar
• T.N. Sindhu, N. Feroze, and M. Aslam, Bayesian analysis of the Kumaraswamy distribution under failure censoring sampling scheme, Int. J. Adv. Sci. Tech. 51 (2013), pp. 1–12.
   Google Scholar
• S.K. Singh, U. Singh, and M. Kumar, Bayesian estimation for Poisson-exponential model under progressive type-II censoring data with binomial removal and its application to ovarian cancer data, Commun. Stat. Simul. Comput. 45 (2016), pp. 3457–3475.
   Web of Science ®Google Scholar
• F. Sultana, Y.M. Tripathi, and M.K. Rastogi, Parameter estimation for the Kumaraswamy distribution based on hybrid censoring, Am. J. Math. Manage. Sci. 37 (2018), pp. 243–261.
   Google Scholar
• L. Wang, Estimation for exponential distribution based on competing risk middle censored data, Commun. Stat. - Theory Methods. 45 (2016), pp. 2378–2391.
   Web of Science ®Google Scholar
• L. Wang, Inference of progressively censored competing risks data from Kumaraswamy distributions, J. Comput. Appl. Math. 343 (2018), pp. 719–736.
   Web of Science ®Google Scholar
• L. Wang, Inference for Weibull competing risks data under generalized progressive hybrid censoring, IEEE Trans. Reliab. 67 (2018), pp. 998–1007.
   Web of Science ®Google Scholar