:: Volume 2, Issue 2 (3-2006) ::
JSRI 2006, 2(2): 129-140 Back to browse issues page
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
Mohammad Jafari Jozani *
, m.j.jozani@srtc.ac.ir
Abstract:   (2749 Views)

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]

Keywords: minimax estimation, restricted parameter space, squared log error loss, binomial distribution, lower bounded parameter space, two­point prior.
Full-Text [PDF 367 kb]   (688 Downloads)    
Type of Study: Research | Subject: General
Received: 2016/02/10 | Accepted: 2016/02/10 | Published: 2016/02/10

XML   Persian Abstract   Print

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 2, Issue 2 (3-2006) Back to browse issues page