Optimum design of nonlinear experiments based on linear Bayesian estimators

Rok, strany: 2003, 69 - 77

In a nonlinear regression model, the linear Bayesian estimator is shown to minimize the mean square error matrix (MSE). The inverse of MSE is proved to be a concave function of the design. Thus optimality criteria applied to MSE could lead to convex Bayesian design methods.

ISO 690:

Hornišová, K., Pázman, A. 2003. Optimum design of nonlinear experiments based on linear Bayesian estimators. In Tatra Mountains Mathematical Publications, vol. 26, no.1, pp. 69-77. 1210-3195.

APA:

Hornišová, K., Pázman, A. (2003). Optimum design of nonlinear experiments based on linear Bayesian estimators. Tatra Mountains Mathematical Publications, 26(1), 69-77. 1210-3195.