cv.SVTApproxImpute: CV for SVTApproxImpute

In jeffwong/imputation: imputation

Description

Cross Validation for SVT Imputation Artificially erase some data and run SVTImpute multiple times, varying lambda using lambda.range. For each lambda, compute the RMSE on the subset of x for which data was artificially erased.

Usage

  cv.SVTApproxImpute(x,
    lambda.range = seq(0, 1, length.out = 101),
    parallel = F)

Arguments

x	a data frame or matrix where each row represents a different record
lambda.range	a vector of penalty terms to use in the CV
parallel	runs each run for lambda in lambda.range in parallel. Requires a parallel backend to be registered

Examples

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

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