The Binomial Parameter Estimation by Using Weighted Method of Two Bayesian Estimators

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Wararit Panichkitkosolkul

Abstract

This paper proposes a new binomial parameter estimation by using the Weighted
method of two Bayesian estimators: Bayesian estimator given Beta(1/2,1/2) prior distribution
and Bayesian estimator given Beta(2,2) prior distribution. The used weighted value has the
minimum variance of the estimator. In addition, this research compares three parameter
estimation methods. These methods are: Bayesian method given Beta(1/2,1/2) prior
distribution (B1), Bayesian method given Beta(2,2) prior distribution (B2), and Weighted
method of two Bayesian estimators (W). Monte Carlo simulation is used to investigate the
behavior of this new binomial parameter estimation based on mean square errors (MSE).
Simulation results are as follows: For all sample sizes, the MSE of B1 method is the lowest
when p \fn_phv \leq 0.20 and the MSE of B2 method is the lowest when 0.30 \fn_phv < p \fn_phv < 0.50 . For the
sample sizes at least 50, The MSE of W method is the lowest when p is equal to 0.25.

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How to Cite
Panichkitkosolkul, W. (1). The Binomial Parameter Estimation by Using Weighted Method of Two Bayesian Estimators. Science & Technology Asia, 14(2), 35-41. Retrieved from https://www.tci-thaijo.org/index.php/SciTechAsia/article/view/41365
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