1. Mean squared error of prediction as a criterion for evaluating and comparing system models
- Author
-
Daniel Wallach and Bruno Goffinet
- Subjects
0106 biological sciences ,Mean squared error ,Ecological Modeling ,Mean squared prediction error ,Process (computing) ,04 agricultural and veterinary sciences ,01 natural sciences ,Bayesian information criterion ,Statistics ,040103 agronomy & agriculture ,0401 agriculture, forestry, and fisheries ,Model quality ,Error detection and correction ,010606 plant biology & botany ,Mathematics - Abstract
Model evaluation is an essential aspect of the process of development of system models. When the main purpose of the model is prediction, a reasonable criterion of model quality is the mean squared error of prediction. This criterion is defined here, and it is shown how it can be estimated from available data in a number of situations, including the situation where the parameters of the model are adjusted to the data. An example of the use of this criterion for choosing between alternative models is presented.
- Published
- 1989
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