On bayesian D-optimum design criteria and the equivalence theorem in non-linear models

D. Firth; J. P. Hinde

doi:10.1111/1467-9868.00096

On bayesian D-optimum design criteria and the equivalence theorem in non-linear models

D. Firth, J. P. Hinde

Research output: Contribution to a Journal (Peer & Non Peer) › Article › peer-review

22 Citations (Scopus)

Abstract

The concavity of some Bayesian D-optimality criteria is investigated and is found in some cases to depend on the prior distribution. In the case of a non-concave criterion, the standard equivalence theorem may fail, but a local version continues to apply.

Original language	English
Pages (from-to)	793-797
Number of pages	5
Journal	Journal of the Royal Statistical Society. Series B: Statistical Methodology
Volume	59
Issue number	4
DOIs	https://doi.org/10.1111/1467-9868.00096
Publication status	Published - 1997
Externally published	Yes

Keywords

Concavity
Equivalence theorem
Optimum design of experiments

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10.1111/1467-9868.00096

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abstract = "The concavity of some Bayesian D-optimality criteria is investigated and is found in some cases to depend on the prior distribution. In the case of a non-concave criterion, the standard equivalence theorem may fail, but a local version continues to apply.",

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KW - Equivalence theorem

KW - Optimum design of experiments

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DO - 10.1111/1467-9868.00096

M3 - Article

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On bayesian D-optimum design criteria and the equivalence theorem in non-linear models

Abstract

Keywords

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