Parameter neutral optimum design for non-linear models

被引:9
|
作者
Firth, D [1 ]
Hinde, JP [1 ]
机构
[1] UNIV EXETER,EXETER EX4 4QJ,DEVON,ENGLAND
关键词
Bayesian design; D-optimality; equivalence theorem; G-optimality; invariance; Jeffreys prior; logistic regression; non-linear model;
D O I
10.1111/1467-9868.00097
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
Some Bayesian approaches to D-optimum design of experiments are considered from the viewpoint of invariance under reparameterization of the underlying statistical model. An invariant criterion is proposed which does not require the detailed specification of a prior, and which is shown to be equivalent to G-optimality under a Jeffreys prior. The methods are applied and discussed in the contexts of exponential decay and quantal response models.
引用
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页码:799 / 811
页数:13
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