Parameter estimation of two-parameter Rayleigh distribution under progressive censoring with binomial removals
Subject Areas : StatisticsNilofar Asle Fallah 1 , Akram Kohansal 2 , Ramin Kazemi 3
1 - Department of Statistics, Imam Khomeini International University, Qazvin, Iran
2 - Department of Statistics, Imam Khomeini International University, Qazvin, Iran
3 - Department of Statistics, Imam Khomeini International University,Qazvin, Iran
Keywords: زمان مورد انتظار آزمایش, توزیع رایلی دوپارامتری, سانسور فزاینده نوع 2, حذف دوجملهای,
Abstract :
The estimation of unknown parameters of two-parameter Rayleigh distribution based on Type-II progressive censoring with binomial removals is studied. Maximum likelihood estimators of the parameters and their confidence intervals are derived. By applying Markov Chain Monte Carlo techniques, Bayes estimators, and corresponding highest posterior density confidence intervals of parameters are obtained. The expected time required to complete the life test under this censoring scheme is investigated. Monte Carlo simulations are performed to compare the performances of the different methods, and one data set is analyzed for illustrative purposes. - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
[1] J. W. S. Rayleigh. On the resultant of a large number of vibrations of the some pitch and of arbitrary phase. Philosophical Magazine, 5-th Series 10:73-78(1880).
[2] S. Dey, T. Dey, D. Kundu. Two-parameter Rayleigh distribution: different methods of estimation. American Journal of Mathematical and Management Sciences 33: 55-74(2014).
[3] A. Kohansal, S. Rezakhah. Inference of for two-parameter Rayleigh distribution based on progressively censored samples. Statistics 53: 81-100(2019).
[4] R. Hashemi, L. Amiri. Analysis of progressive Type-II censoring in the Weibull model for competing risks data with binomial removals. Applied Mathematical Sciences5:1073-1087(2011).
[5] M. Mubarak. Parameter Estimation Based on the Frèchet Progressive Type II Censored Data with Binomial Removals. International Journal of Quality, Statistics, and Reliability DOI: 10.1155/ 2012/ 245910 (2012).
[6]R.Azimi, F. Yaghmaei. Bayesian estimation based on Rayleigh progressive Type-II censored data with binomial removals. Journal of Quality and Reliability Engineering DOI: 10.1155/ 2013/ 896807 (2013)
[7] A. Kohansal. Statistical analysis of two-parameter bathtub-shaped lifetime distribution under progressive censoring with binomial removals. Gazi University Journal of Science 29: 783–792 (2016).
[8] J. H. Cao, K. Chen. An introduction to the reliability mathematics. Beijing: Higher Education Press (2006).
[9] N. L. Johnson, S. Kotz, N. Balakrishnan. Continuous Univariate Distributions. 2nd ed., Wiley, NewYork (1994).
[10] L. Devroye. A simple algorithm for generating random variates with a log-concave density. Computing 33:247-257 (1984).
[11] N. Balakrishnan, R. Aggarwala. Progressive censoring: theory, methods and applications. Birkhauser, Boston (2000).
[12] J. Lieblein, M. Zelen. Statistical investigation of the fatigue life of deep-groove ball bearings. Journal of Research of the National Bureau of Standards 57:273-316 (1956).
[13] M. Z. Raqab. Inference for generalized exponential distribution based on record statistics. Journal of Statistical Planning and Inference 104:339-350 (2002).
[14] C. Kim, K. Han. Estimation of the scale parameter of the Rayleigh distribution under general progressive censoring. Journal of the Korean Statistical Society 38:239-246 (2009).