R: Matrix Completion via Iterative Soft-Thresholded SVD

# Matrix Completion via Iterative Soft-Thresholded SVD

## Documentation for package ‘softImpute’ version 1.4

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

%*%-method | Class '"SparseplusLowRank"'
as.matrix-method | Class '"Incomplete"'
as.matrix-method | Class '"SparseplusLowRank"'
biScale | standardize a matrix to have optionally row means zero and variances one, and/or column means zero and variances one.
coerce-method | Class '"Incomplete"'
coerce-method | create a matrix of class 'Incomplete'
colMeans-method | Class '"SparseplusLowRank"'
colSums-method | Class '"SparseplusLowRank"'
complete | make predictions from an svd object
complete-method | make predictions from an svd object
deBias | Recompute the '$d' component of a '"softImpute"' object through regression.
dim-method | Class '"SparseplusLowRank"'
impute | make predictions from an svd object
Incomplete | create a matrix of class 'Incomplete'
Incomplete-class | Class '"Incomplete"'
lambda0 | compute the smallest value for 'lambda' such that 'softImpute(x,lambda)' returns the zero solution.
lambda0-method | compute the smallest value for 'lambda' such that 'softImpute(x,lambda)' returns the zero solution.
norm-method | Class '"SparseplusLowRank"'
rowMeans-method | Class '"SparseplusLowRank"'
rowSums-method | Class '"SparseplusLowRank"'
softImpute | impute missing values for a matrix via nuclear-norm regularization.
SparseplusLowRank-class | Class '"SparseplusLowRank"'
splr | create a 'SparseplusLowRank' object
svd.als | compute a low rank soft-thresholded svd by alternating orthogonal ridge regression
svd.als-method | compute a low rank soft-thresholded svd by alternating orthogonal ridge regression