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An R package to make imputation simple. Currently supported methods include

• Model based (optionally add [non-]parametric random residual)
  • linear regression
  • robust linear regression (M-estimation)
  • ridge/elasticnet/lasso regression (from version >= 0.2.1)
  • CART models
  • Random forest
• Model based, multivariate
  • Imputation based on EM-estimated parameters (from version >= 0.2.1)
  • missForest (from version >= 0.2.1)
• Donor imputation (including various donor pool specifications)
  • k-nearest neigbour (based ongower's distance)
  • sequential hotdeck (LOCF, NOCB)
  • random hotdeck
  • Predictive mean matching
• Other
  • (groupwise) median imputation (optional random residual)
  • Proxy imputation (copy from other variable)

To install simputation and all packages needed to support various imputationmodels do the following.

install.packages("simputation",dependencies=TRUE)

To install the development version.

git clone https://github.com/markvanderloo/simputationmake install

Create some data suffering from missings

library(simputation)# current packagedat<-iris# empty a few fieldsdat[1:3,1]<-dat[3:7,2]<-dat[8:10,5]<-NAhead(dat,10)

Now imputeSepal.Length andSepal.Width by regression onPetal.Length andSpecies, and imputeSpecies using a CART model, that uses all other variables (including the imputed variables in this case).

dat|>  impute_lm(Sepal.Length+Sepal.Width~Petal.Length+Species)|>  impute_cart(Species~.)|># use all variables except 'Species' as predictor  head(10)

• The introductoryvignette
• slides from myuseR2017 talk.