Bayesian Estimation of Rare Sensitive Attribute

Authors

  • Abdul Wakeel - Department of Mathematics, COMSATS Institute of Information Technology, Park Road Chak Shahzad, Islamabad, Pakistan. - Department of Statistics, Faculty of Natural Sciences, Quaid-i-Azam University, Islamabad, Pakistan.
  • Muhammad Aslam Department of Statistics, Faculty of Natural Sciences, Quaid-i-Azam University, Islamabad, Pakistan.

Keywords:

Bayesian estimation, maximum likelihood estimator, mean squares error, rare sensitive attribute, simple random sampling

Abstract

In this study, a Bayesian estimation of the population mean of a rare sensitive attribute has been considered and a Bayes estimator is proposed when the information from the respondent is collected through the randomized response technique (RRT) using Greenberg et al. (1969) and Land et al. (2012) models. The Gamma distribution has been used as prior information to check the behaviour of the Bayes estimator for the different values of population mean of rare sensitive and rare unrelated attribute. It is noted that Bayes estimator is efficient as compared to the Maximum Likelihood Estimator (MLE).

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How to Cite

Wakeel, A., & Aslam, M. (2015). Bayesian Estimation of Rare Sensitive Attribute. Thailand Statistician, 11(1), 17–29. Retrieved from https://ph02.tci-thaijo.org/index.php/thaistat/article/view/34214

Issue

Vol. 11 No. 1 (2013): JANUARY

Section

Articles