R: A General Multivariate Imputation Framework

# A General Multivariate Imputation Framework

## Documentation for package ‘imputeR’ version 2.2

- DESCRIPTION file
- Package NEWS
- Package README

## Help Pages

imputeR-package | imputeR-package description
CubistR | Cubist method for imputation
Detect | Detect variable type in a data matrix
gbmC | boosting tree for imputation
glmboostR | Boosting for regression
guess | Impute by (educated) guessing
impute | General Imputation Framework in R
lassoC | logistic regression with lasso for imputation
lassoR | LASSO for regression
major | Majority imputation for a vector
mixError | Calculate mixed error when the imputed matrix is mixed type
mixGuess | Naive imputation for mixed type data
mr | calculate miss-classification error
orderbox | Ordered boxplot for a data matrix
parkinson | Parkinsons Data Set
pcrR | Principle component regression for imputation
plotIm | Plot function for imputation
plsR | Partial Least Square regression for imputation
ridgeC | Ridge regression with lasso for imputation
ridgeR | Ridge shrinkage for regression
Rmse | calculate the RMSE or NRMSE
rpartC | classification tree for imputation
SimEval | Evaluate imputation performance by simulation
SimIm | Introduce some missing values into a data matrix
spect | SPECT Heart Data Set
stepBackC | Best subset for classification (backward)
stepBackR | Best subset (backward direction) for regression
stepBothC | Best subset for classification (both direction)
stepBothR | Best subset for regression (both direction)
stepForC | Best subset for classification (forward direction)
stepForR | Best subset (forward direction) for regression
tic | Insurance Company Benchmark (COIL 2000) Data Set