Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!
Get Started for Free

plotIm

Plot function for imputation


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

A General Multivariate Imputation Framework

v2.2
GPL-3
Authors
Steffen Moritz [aut, cre] (<https://orcid.org/0000-0002-0085-1804>), Lingbing Feng [aut], Gen Nowak [ctb], Alan. H. Welsh [ctb], Terry. J. O'Neill [ctb]
Initial release
2020-01-20

We don't support your browser anymore

Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.