A General Multivariate Imputation Framework

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 |

imputeR-package | imputeR-package description |

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 |

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