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BAYESIAN ESTIMATION OF WEIBULL-G-WEIBULL DISTRIBUTION FOR CENSORED DATA USING M-H ALGORITHM
Keywords:
Weibull-G-Weibull distribution, right censoring, Bayesian estimation, M-H algorithm, SELF, LINEXDOI:
https://doi.org/10.17654/0972361724058Abstract
The main objective of this paper is to estimate the parameters of Weibull-G-Weibull distribution using the Bayesian approach for Type I and Type II censoring based on the Metropolis-Hastings (M-H) algorithm. Comparison is made through the SELF and LINEX loss functions. It is found that for scale parameter $\theta$ and shape parameter $\gamma$, the SELF loss function performs better, while for the shape parameters $\alpha$ and $\beta$, the LINEX loss function performs better for fixed time and censorship percentages.
Received: March 14, 2024
Accepted: June 11, 2024
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