Bayes Estimation Based on Random Censored Data for Some Life Time Models Under Symmetric and Asymmetric Loss Functions

Abstract

Censored data arise naturally in a number of fields, particularly in problems of reliability and survival analysis. There are several types of censoring; in this article, we shall confine ourselves to the right randomly censoring type. Under the Bayesian framework, we study the estimation of parameters in a general framework based on the random censored observations under Linear-Exponential (LINEX) and squared error loss (SEL) functions. As a special case, Weibull model is discussed and the admissibility of estimators of parameters verified. Finally, a simulation study is conducted based on Monte Carlo (MC) method for comparing estimated risks of the estimators obtained.

Keywords:

• Bayes estimation
• Life time models
• Lindley's approximation
• LINEX loss function
• Random censoring

Mathematics Subject Classification:

• 62N02
• 62F15
• 62C15

Acknowledgments

The authors are grateful to the Associate Editor and two anonymous referees for making many helpful comments and suggestions on an earlier version of this article. Doostparast's research was supported by a grant from Ferdowsi University of Mashhad (No. MS86084DSP). Parsian's research was supported by a grant of the Research Council of the University of Tehran.