%0 Journal Article
%A Jafari Jozani, Mohammad
%T Admissible and Minimax Estimator of the Parameter $theta$ in a Binomial $Bin( n ,theta)$ distribution under Squared Log Error Loss Function in a Lower Bounded Parameter Space
%J Journal of Statistical Research of Iran
%V 2
%N 2
%U http://jsri.srtc.ac.ir/article-1-153-en.html
%R
%D 2006
%K minimax estimation, restricted parameter space, squared log error loss, binomial distribution, lower bounded parameter space, twopoint prior.,
%X Extended Abstract. The study of truncated parameter space in general is of interest for the following reasons: 1.They often occur in practice. In many cases certain parameter values can be excluded from the parameter space. Nearly all problems in practice have a truncated parameter space and it is most impossible to argue in practice that a parameter is not bounded. In truncated parameter space, the commonly used estimators of $theta$ such as the maximum likelihood estimators are inadmissible. Even more characteristic is the fact that boundary rules are mostly inadmissible, where a boundary estimator is an estimator which takes, with positive probability for some ...[To continue please click here]
%> http://jsri.srtc.ac.ir/article-1-153-en.pdf
%P 129-140
%& 129
%!
%9 Research
%L A-10-1-123
%+
%G eng
%@ 1735-1294
%[ 2006