@article{JSSv015i10, title={CVTresh: R Package for Level-Dependent Cross-Validation Thresholding}, volume={15}, url={https://www.jstatsoft.org/index.php/jss/article/view/v015i10}, doi={10.18637/jss.v015.i10}, abstract={The core of the wavelet approach to nonparametric regression is thresholding of wavelet coefficients. This paper reviews a cross-validation method for the selection of the thresholding value in wavelet shrinkage of Oh, Kim, and Lee (2006), and introduces the R package CVThresh implementing details of the calculations for the procedures. This procedure is implemented by coupling a conventional cross-validation with a fast imputation method, so that it overcomes a limitation of data length, a power of 2. It can be easily applied to the classical leave-one-out cross-validation and K-fold cross-validation. Since the procedure is computationally fast, a level-dependent cross-validation can be developed for wavelet shrinkage of data with various sparseness according to levels.}, number={10}, journal={Journal of Statistical Software}, author={Kim, Donghoh and Oh, Hee-Seok}, year={2006}, pages={1–13} }