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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

Install

install.packages('denoiseR')

Monthly Downloads

177

Version

1.0.2

License

GPL (>= 2)

Maintainer

Julie Josse

Last Published

February 26th, 2020

Functions in denoiseR (1.0.2)

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