Estimation of Parameters in a Bivariate Generalized Exponential Distribution Based on Type-II Censored Samples
- Title
- Estimation of Parameters in a Bivariate Generalized Exponential Distribution Based on Type-II Censored Samples
- Author
- 김성욱
- Keywords
- Bayesian estimation; Dependence measure; Maximum likelihood estimation; Monte Carlo simulation; Numerical method; 62F10; 62F15; 62H12; EM ALGORITHM; KENDALLS TAU
- Issue Date
- 2016-03
- Publisher
- TAYLOR & FRANCIS INC
- Citation
- COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, v. 45, No. 10, Page. 3776-3797
- Abstract
- In this article, we discuss the maximum likelihood estimation and Bayesian estimation procedures for estimating the parameters in an absolute continuous bivariate generalized exponential distribution based on Type-II censored samples. A Markov chain Monte Carlo method is applied to compute the Bayes estimates. We also propose a method to obtain the initial estimates of the parameters for the required iterative algorithm. A simulation study is used to evaluate the performance of the proposed estimation procedures. Two real data examples are utilized to illustrate the methodology developed in this manuscript.
- URI
- https://www.tandfonline.com/doi/abs/10.1080/03610918.2015.1130834http://hdl.handle.net/20.500.11754/50488
- ISSN
- 0361-0918; 1532-4141
- DOI
- 10.1080/03610918.2015.1130834
- Appears in Collections:
- COLLEGE OF SCIENCE AND CONVERGENCE TECHNOLOGY[E](과학기술융합대학) > APPLIED MATHEMATICS(응용수학과) > Articles
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