SVTImpute: SVT Imputation

In jeffwong/imputation: imputation

Description

Imputation using Singular Value Thresholding a la Cai, Candes, Shen.

Usage

  SVTImpute(x, lambda, stepsize, threshold = 0.001,
    max.iters = 10, verbose = F)

Arguments

x	a data frame or matrix with size n1 x n2 where each row represents a different record
lambda	the penalty on the singular values
stepsize	optional. If not provided, uses 1.2 * (n1 * n2) / (number of missing elements)
threshold	convergence threshold
max.iters	maximum number of iterations. Note that each iteration will require computing an SVD
verbose	if TRUE print status updates

References

A Singular Value Thresholding Algorithm for Matrix Completion. Cai, Candes, Shen.

Examples

x = matrix(rnorm(100),10,10)
  x.missing = x > 1
  x[x.missing] = NA
  SVTImpute(x, 3)

jeffwong/imputation documentation built on May 19, 2019, 4:02 a.m.