plotIm: Plot function for imputation

In imputeR: A General Multivariate Imputation Framework

Description

this is a plot function for assessing imputation performance given the imputed data and the original true data

Usage

plotIm(imp, mis, true, ...)

Arguments

imp	the imputed data matrix
mis	the missing data matrix
true,	the true data matrix
...	other arguments that can be passed to plot

Value

a plot object that show the imputation performance

Examples

data(parkinson)
# introduce 10% random missing values into the parkinson data
missdata <- SimIm(parkinson, 0.1)

# impute the missing values by LASSO
impdata <- impute(missdata, lmFun = "lassoR")

# calculate the normalised RMSE for the imputation
Rmse(impdata$imp, missdata, parkinson, norm = T)

# Plot imputation performance
plotIm(impdata$imp, missdata, parkinson)

imputeR documentation built on Jan. 21, 2020, 1:06 a.m.