Estimating the Average Worth of a Subset Selected from Binomial Populations

Volume 3, Issue 2, pp 236--245 http://dx.doi.org/10.22436/jmcs.03.02.15

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Authors

Riyadh Al-Mosawi - Department of Mathematics, Thiqar University, Thiqar, Iraq

Abstract

Suppose \(\overline{X}=(\overline{X}_1,...\overline{X}_p), (p\geq 2)\); where \(\overline{X}_i\)represents the mean of a random sample of size ni drawn from binomial \(bin(1,\theta_i)\) population. Assume the parameters \(\theta_1,...,\theta_p\) are unknown and the populations \(bin(1,\theta_1),...,bin(1,\theta_p)\) are independent. A subset of random size is selected using Gupta's (Gupta, S. S. (1965). On some multiple decision(selection and ranking) rules. Technometrics 7,225-245) subset selection procedure. In this paper, we estimate of the average worth of the parameters for the selected subset under squared error loss and normalized squared error loss functions. First, we show that neither the unbiased estimator nor the risk- unbiased estimator of the average worth (corresponding to the normalized squared error loss function) exist based on a single-stage sample. Second, when additional observations are available from the selected populations, we derive an unbiased and risk-unbiased estimators of the average worth and also prove that the natural estimator of the average worth is positively biased. Finally, the bias and risk of the natural, unbiased and risk-unbiased estimators are computed and compared using Monti Carlo simulation method.

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Keywords

• binomial populations
• selected subset
• average worth estimation

MSC

•  62L12
•  62F10
•  62F07

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