In spline theory, the generalized cross validation (GCV) technique has proved to be an effective (though rather slow) statistical way for estimating this optimum. On the other hand, wavelet theory is well suited for signal and image processing. This paper investigates the possibility of using ...
3) Generalized cross validation 广义交叉验证 1. And then generalized cross validation(GCV) was introduced to get asymptotic optimal thresholds without estimating noise variance. 该算法基于全变差构建复Bandelet寻优的目标函数;采用广义交叉验证准则,在不需要估计噪声方差的情况下,自适应获取各个分解层的渐进...
1.And then generalized cross validation(GCV) was introduced to get asymptotic optimal thresholds without estimating noise variance.该算法基于全变差构建复Bandelet寻优的目标函数;采用广义交叉验证准则,在不需要估计噪声方差的情况下,自适应获取各个分解层的渐进最优阈值。 2.The optimal threshold function,in the...
Consider the ridge estimate () for in the model unknown, () = (XTX + nI)1XTy. We study the method of generalized cross-validation (GCV) for choosing a good value for from the data. The estimate is the minimizer of V() given by关键词: Ridge regression Cross-validation Ridge parameter...
1130]. F. O'Sullivan also presents plots of cross- validation functions that arise in system identi cation problems 27, p. 1277]. We would also like to mention Fig. 2 in 14, p. 222] and Fig. 4.10 in 43, p. 60]. Finally, some limitations of the GCV method are mentioned in 39,...
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We also present experiments with integer wavelet transforms, and illustrate the method with some results in image denoising. keywords: noise reduction, wavelets, threshold, generalized cross validation 1 Introduction Wavelet thresholding is a straightforward though effective method in nonparam... 展开 ...
To this date, data driven tuning method for divide-and-conquer kernel ridge regression (d-KRR) has been lacking in the literature, which limits the applicability of d-KRR for large data sets. In this paper, by modifying the Generalized Cross-validation (GCV, Wahba, 1990) score, we ...
Using generalized cross-validation (GCV, [Craven and Wahba, 1979]), a smoothing parameter is chosen that can further reduce the roughness in the spline component. Based on the original knots and the estimated smoothing parameter, each additive effect can be described by its effective degrees of ...
These Fortran-77 subroutines provide building blocks for Generalized Cross-Validation (GCV) (Craven and Wahba, 1979) calculations in data analysis and data smoothing including ridge regression (Golub, Heath, and Wahba, 1979), thin plate smoothing splines (Wahba and Wendelberger, 1980), deconvolution...