Small size designs in nonlinear models computed by stochastic optimization

被引：0

作者：

Gauchi, JP ^{[1
]}

Pázman, A ^{[1
]}

机构：

[1] INRA, Biometr Unit, Jouy En Josas, France

来源：

MODA 7 - ADVANCES IN MODEL-ORIENTED DESIGN AND ANALYSIS, PROCEEDINGS | 2004年

关键词：

A- and D-optimality; distribution of estimators; Mean Square Error;

D O I：

暂无

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

Optimality criteria, that are functions of the mean square error matrix, are expressed as integrals of the density of the parameter estimator. The optimum design is obtained by an accelerated stochastic optimization method. The estimator is modified to reflect prior knowledge about the parameters, and to take into account the boundary of the parameter space. Results of Pazman and Pronzato (1992) are extended and improved by that. Computer results are presented on examples.

引用

页码：71 / 79

页数：9

共 16 条

[1] A DYNAMIC APPROACH TO PREDICTING BACTERIAL-GROWTH IN FOOD [J].