Title of article :
Robust designs for probability estimation in binary response experiments
Author/Authors :
Huang، نويسنده , , Shih-Hao and Huang، نويسنده , , Mong-Na Lo، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2014
Abstract :
The purpose of this work is to investigate robust design problems for estimation of the response probability curve under binary response experiments with model uncertainty consideration. A minimax type of model robust design criterion, called WB-optimum in short is proposed, based on minimization of the maximum of the weighted squared probability bias function under two rival models. The corresponding design issues are investigated and results under the above design criterion for given rival models with several commonly seen symmetric links are presented.
Keywords :
Compromise weight functions , Equal oscillation , LOGIT MODEL , Probit Model , Minimax optimality , model discrimination , WB-optimum
Journal title :
Journal of Statistical Planning and Inference
Journal title :
Journal of Statistical Planning and Inference