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This article considers the traditional figures of merit (FOMs), namely bias, and mean squared (prediction) error, that are typically used to evaluate simulation experiments. We propose functions of them that account for different variables' units; these alternative FOMs 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.