imputation (version 2.0.3)

cv.SVTApproxImpute: CV for SVTApproxImpute

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)