ridge.diacomp: Calculation of Generalized Cross-validation

Description

This function calculates generalized cross-validation for ridge regression.

Usage

1
ridge.diacomp(out.ls, obs, lam) 

Arguments

out.ls

an object of class ‘lsfit’

obs

observations

lam

smoothing parameter for penalized least squares method

Details

This function calculates generalized cross-validation for ridge regression.

Value

rsq

R-squared

gcv

generalized cross-validation for ridge regression.

df

degree of freedom

References

Oh, H-S. (1999) Spherical wavelets and their statistical analysis with applications to meteorological data. Ph.D. Thesis, Department of Statistics, Texas A\&M University, College Station.

Li, T-H. (1999) Multiscale representation and analysis of spherical data by spherical wavelets. SIAM Journal on Scientific Computing, 21, 924–953.

Oh, H-S. and Li, T-H. (2004) Estimation of global temperature fields from scattered observations by a spherical-wavelet-based spatially adaptive method. Journal of the Royal Statistical Society Ser. B, 66, 221–238.

See Also

gcv.lambda, ridge.comp.


Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

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