AU - Jafari Jozani, Mohammad
TI - 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
PT - JOURNAL ARTICLE
TA - srtc-jsri
JN - srtc-jsri
VO - 2
VI - 2
IP - 2
4099 - http://jsri.srtc.ac.ir/article-1-153-en.html
4100 - http://jsri.srtc.ac.ir/article-1-153-en.pdf
SO - srtc-jsri 2
AB - 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]
CP - IRAN
IN -
LG - eng
PB - srtc-jsri
PG - 129
PT - Research
YR - 2006