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