Bayes estimation of success probability under different priors information
LI Xiao-kan · Journal of Shaanxi University of Technology · 2014
Bayes estimation of parameter depends on the prior distribution and the loss function. Bayes estimation is the mean of the posterior distribution under the square loss. The paper first provided the Bayes estimation of success probability under the condition of zero information priori,Jeffreys priori and square loss, and then compared the properties of unbiasedness,variance and MSE and risks,and the numerical simulation was also experimented. The result showed that the estimation under zero information priori is better than the estimation under Jeffreys priori. The MSE of the estimation under non-informative priori is smaller than the estimation under Jeffreys priori and the risk of the estimation under non-informative priori is better than the estimation under Jeffreys priori.