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Smoothing Parameter Selection Using Multifold Cross-Validation in Smoothing Spline Regressions
Smoothing Parameter Selection Using Multifold Cross-Validation in Smoothing Spline Regressions
- 한국통계학회
- Communications for Statistical Applications and Methods
- Vol.5 No.2
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1998.01277 - 285 (9 pages)
- 0
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The smoothing parameter <TEx>$\lambda$</TEx> in smoothing spline regression is usually selected by minimizing cross-validation (CV) or generalized cross-validation (GCV). But, simple CV or GCV is poor candidate for estimating prediction error. We defined MGCV (Multifold Generalized Cross-validation) as a criterion for selecting smoothing parameter in smoothing spline regression. This is a version of cross-validation using $leave-\kappa-out$ method. Some numerical results comparing MGCV and GCV are done.
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