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An -Square Coefficient Based on Final Prediction Error by Valentin Rousson; Nicoleta Francisca Goşoniu is a Mathematics article available to read on EtoBox.

What is An -Square Coefficient Based on Final Prediction Error about?

In this paper, we propose an R 2 coefficient to measure the percentage of variance which can be explained by the fitted model (not by the true model) in a multiple linear regression problem. This new coefficient, denoted R 2 FPE , is a reparametrization of the FPE criterion in use for model selection, such that maximizing R 2 FPE over a set of candidate models is the same as minimizing FPE. Thus, R 2 FPE can be used simultaneously for assessing goodness of fit and for model selection. At each step of a model selection procedure, the user can then quantify what is gained/lost when adding/removing a variable in/from the model, which should facilitate practice and comprehension of model selection.

Who reads An -Square Coefficient Based on Final Prediction Error?

It is typically read by researchers, students, and practitioners in Mathematics.

Author
Valentin Rousson; Nicoleta Francisca Goşoniu
Publisher
Elsevier Science; Elsevier ; Elsevier BV (ISSN 1572-3127)
Published
2007
Language
EN
Field
Mathematics (Physical Sciences)

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