Mean squared prediction error: Difference between revisions

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Revision as of 19:07, 30 May 2018

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[[Colin Mallows]] advocated this method in the construction of his model selection statistic [[Mallows's Cp|''C_p'']], which is a normalized version of the estimated MSPE:

:<math>n\cdot C_p=\frac{\sum_{i=1}^n\left(y_i-\widehat{g}(x_i)\right)^2}{\widehat{\sigma}^2}-n+\operatorname{tr}\left[L\right]2p.</math>

where ''p'' comes from the fact that the number of estimated parameters ''p'' estimated for a parametric smoother is given byand <math>p=\operatornamewidehat{tr\sigma}\left[L\right]^2</math>, andis ''C''computed isfrom inthe honorversion of [[Cuthbertthe Daniel]].{{citationmodel needed|date=Marchthat 2013}}includes all possible regressors.

==See also==