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denoiseR (version 1.0.2)
Regularized Low Rank Matrix Estimation
Description
Estimate a low rank matrix from noisy data using singular values thresholding and shrinking functions. Impute missing values with matrix completion. The method is described in
.
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Version
Version
1.0.2
1.0
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Install
install.packages('denoiseR')
Monthly Downloads
191
Version
1.0.2
License
GPL (>= 2)
Maintainer
Julie Josse
Last Published
February 26th, 2020
Functions in denoiseR (1.0.2)
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LRsim
Low Rank Simulation
Presidents
Contingency table with US Presidents speeches.
imputeada
Adaptive Shrinkage with missing values - Imputation
estim_sigma
Estimate sigma
ISA
Iterated Stable Autoencoder
imputecount
Imputation of count data with the Iterated Stable Autoencoder
optishrink
Optimal Shrinkage
tumors
Brain tumors data.
denoiseR-package
Regularized Low Rank Matrix Estimation
impactfactor
Data set on metrics for scientific journals:
adashrink
Adaptive Shrinkage
estim_delta
Estimates delta for Iterated Stable Autoencoder