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Figures of merit for simultaneous inference and comparisons in simulation experiments

This article considers the traditional figures of merit, namely, bias and mean squared (prediction) error, which are typically used to evaluate simulation experiments. We propose functions of them that account for different variables' units; these alternative figures of merit are closely tied t...

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Bibliographic Details
Published in:Stat (International Statistical Institute) 2015, Vol.4 (1), p.196-211
Main Authors: Cressie, Noel, Burden, Sandy
Format: Article
Language:English
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Summary:This article considers the traditional figures of merit, namely, bias and mean squared (prediction) error, which are typically used to evaluate simulation experiments. We propose functions of them that account for different variables' units; these alternative figures of merit are closely tied to simultaneous multivariate inference on an unknown parameter vector or unknown state vector. Their usefulness is illustrated in a simulation experiment, where the goal is to determine the statistical properties associated with prediction of a multivariate state. Copyright © 2015 John Wiley & Sons, Ltd.
ISSN:2049-1573
2049-1573
DOI:10.1002/sta4.88