Bayesian Optimal Designs for Efficient Estimation of the Optimum Point with Generalised Linear Models
- Guilin Li
- Szu Hui Ng
- Matthias Hwai-yong Tan
DOIAbstract
10.1080/16843703.2018.1542965Quality Technology & Quantitative Management170189-10
10.1080/16843703.2018.1542965Quality Technology & Quantitative Management170189-10
In nonlinear estimation problems with linear models, one difficulty in obtaining optimal designs is ...
The emphasis in this work is on derivation of optimal Bayes inferences and designs in relatively une...
Most of the design work has focused on the linear regression model due to its simplicity. However, a...
Bayesian optimal designs for estimation and prediction in linear regression models are considered. F...
Contents: Part I: Theory. Some History Leading to Design Criteria for Bayesian Prediction; A.C. Atki...
SUMMARY. In a conventional functional linear model, incorporating a Bayesian experimental design, un...
Available from TIB Hannover: RR 8460(2003,10) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Tec...
While Bayesian G- and V-optimal designs for the multinomial logit model have been shown to have bett...
In many areas of science, models are used to describe attributes of complex systems. These models ar...
The Bayesian KL-optimality criterion is useful for discriminating between any two statistical models...
Finding Bayesian optimal designs for nonlinear models is a difficult task because the optimality cri...
Linear minimax estimation and related Bayes-L-optimal design / N. Gaffke ; R. Mathar. - In: Symposiu...
In the context of nonlinear regression models, a new class of optimum design criteria is developed a...
In many areas of science, models are used to describe attributes of complex systems. These models ar...
Recently, Kessels et al. (2006) developed a way to produce Bayesian G- and V-optimal designs for the...
In nonlinear estimation problems with linear models, one difficulty in obtaining optimal designs is ...
The emphasis in this work is on derivation of optimal Bayes inferences and designs in relatively une...
Most of the design work has focused on the linear regression model due to its simplicity. However, a...
Bayesian optimal designs for estimation and prediction in linear regression models are considered. F...
Contents: Part I: Theory. Some History Leading to Design Criteria for Bayesian Prediction; A.C. Atki...
SUMMARY. In a conventional functional linear model, incorporating a Bayesian experimental design, un...
Available from TIB Hannover: RR 8460(2003,10) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Tec...
While Bayesian G- and V-optimal designs for the multinomial logit model have been shown to have bett...
In many areas of science, models are used to describe attributes of complex systems. These models ar...
The Bayesian KL-optimality criterion is useful for discriminating between any two statistical models...
Finding Bayesian optimal designs for nonlinear models is a difficult task because the optimality cri...
Linear minimax estimation and related Bayes-L-optimal design / N. Gaffke ; R. Mathar. - In: Symposiu...
In the context of nonlinear regression models, a new class of optimum design criteria is developed a...
In many areas of science, models are used to describe attributes of complex systems. These models ar...
Recently, Kessels et al. (2006) developed a way to produce Bayesian G- and V-optimal designs for the...
In nonlinear estimation problems with linear models, one difficulty in obtaining optimal designs is ...
The emphasis in this work is on derivation of optimal Bayes inferences and designs in relatively une...
Most of the design work has focused on the linear regression model due to its simplicity. However, a...
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