Characteristics of Bayes Estimator in the Geometric Distribution with Prior Beta

Abstract

Abstract This study aims to examine the unbiased, minimum variance (efficient), and consistent characteristics of Bayes estimator in the Geometric distribution with prior Beta. Based on the results of simulation studies it is found that the Bayes estimator in the Geometric distribution with prior Beta are symptotically unbiased estimator for values θ < 0,5 and is biased for others, are efficient for the number of samples sizes large and values θ ≤ 0,6 and not efficient for others and consistent when value θ ≤ 0,5 and inconsistent for other.