Package: CVThresh 1.1.2

CVThresh: Level-Dependent Cross-Validation Thresholding

The level-dependent cross-validation method is implemented 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.

Authors:Donghoh Kim <[email protected]>, Hee-Seok Oh <[email protected]>

CVThresh_1.1.2.tar.gz
CVThresh_1.1.2.zip(r-4.5)CVThresh_1.1.2.zip(r-4.4)CVThresh_1.1.2.zip(r-4.3)
CVThresh_1.1.2.tgz(r-4.4-any)CVThresh_1.1.2.tgz(r-4.3-any)
CVThresh_1.1.2.tar.gz(r-4.5-noble)CVThresh_1.1.2.tar.gz(r-4.4-noble)
CVThresh_1.1.2.tgz(r-4.4-emscripten)CVThresh_1.1.2.tgz(r-4.3-emscripten)
CVThresh.pdf |CVThresh.html
CVThresh/json (API)

# Install 'CVThresh' in R:
install.packages('CVThresh', repos = c('https://dkimstatlab.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • ipd - Inductance plethysmography data

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.04 score 11 scripts 233 downloads 12 exports 3 dependencies

Last updated 3 years agofrom:8da55e104b. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 13 2024
R-4.5-winOKOct 13 2024
R-4.5-linuxOKOct 13 2024
R-4.4-winOKOct 13 2024
R-4.4-macOKOct 13 2024
R-4.3-winOKOct 13 2024
R-4.3-macOKOct 13 2024

Exports:cvimpute.by.waveletcvimpute.image.by.waveletcvtypecvtype.imagecvwaveletcvwavelet.after.imputecvwavelet.imagecvwavelet.image.after.imputedoppfg1heavppoly

Dependencies:EbayesThreshMASSwavethresh