CVThresh: Level-Dependent Cross-Validation Thresholding
This package carries out level-dependent cross-validation method for the selection of thresholding value in wavelet shrinkage. This procedure is implemented by coupling a conventional cross validation with an imputation method due to a limitation of data length, a power of 2. It can be easily applied to classical leave-one-out and k-fold cross validation. Since the procedure is computationally fast, a level-dependent cross validation can be performed for wavelet shrinkage of various data such as a data with correlated errors.
- Donghoh Kim <firstname.lastname@example.org>, Hee-Seok Oh <email@example.com>
- Date of publication
- 2013-01-18 10:21:20
- Donghoh Kim <firstname.lastname@example.org>
- GPL (>= 2)
- Imputation by wavelet
- Imputation for two-dimensional data by wavelet
- Level-Dependent Cross-Validation Approach for Wavelet...
- Generating test dataset index for cross-validation
- Generating test dataset index of two-dimensional data for...
- Wavelet reconstruction by level-dependent Cross-Validation
- Cross-Validation Wavelet Shrinkage after imputation
- Wavelet reconstruction of image by level-dependent...
- Cross-Validation Wavelet Shrinkage for two-dimensional data...
- Doppler function
- fg1 function
- Heavisine function
- Inductance plethysmography data
- Piecewise polynomial function
Files in this package