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Weibull-Bayesian Estimation Based on Maximum Ranked Set Sampling with Unequal Samples
Department of Studies in Statistics, University of Mysore, Mysuru, India
Department of Statistics, Maharani’s Science College for Women, Mysuru, India
- 1 Department of Studies in Statistics, University of Mysore, Mysuru, India
- 2 Department of Statistics, Maharani’s Science College for Women, Mysuru, India
Open Journal of Statistics·Volume 06 (2016)·Pages 1028–1036·Published 14 November 2016·DOI10.4236/ojs.2016.66083
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Abstract
A modification of ranked set sampling (RSS) called maximum ranked set sampling with unequal sample (MRSSU) is considered for the Bayesian estimation of scale parameter α of the Weibull distribution. Under this method, we use Linex loss function, conjugate and Jeffreys prior distributions to derive the Bayesian estimate of α. In order to measure the efficiency of the obtained Bayesian estimates with respect to the Bayesian estimates of simple random sampling (SRS), we compute the bias, mean squared error (MSE) and asymptotic relative efficiency of the obtained Bayesian estimates using simulation. It is shown that the proposed estimates are found to be more efficient than the corresponding one based on SRS.
KeywordsBayesian EstimationLoss FunctionMRSSUSRSRSS
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