Description Usage Arguments Details Value References Examples

View source: R/cross-validation-KNN.R

This function calculates the estimated cross-validation prediction error for K nearest-neighbor regression and returns a suitable choice for K.

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`X` |
a numeric design matrix, which used in |

`Dvec` |
a n * 3 binary matrix with three columns, corresponding to the three classes of the disease status. In row i, 1 in column j indicates that the i-th subject belongs to class j, with j = 1, 2, 3. A row of |

`V` |
a binary vector containing the verification status (1 verified, 0 not verified). |

`K.list` |
a list of candidate values for K. If |

`type` |
a type of distance, see |

`plot` |
if |

Data are divided into two groups, the first contains the data corresponding to V = 1, whereas the second contains the data corresponding to V = 0. In the first group, the discrepancy between the true disease status and the KNN estimates of the probabilities of the disease status is computed by varying `K`

from 1 to the number of verification subjects, see To Duc et al. (2016). The optimal value of `K`

is the value that corresponds to the smallest value of the discrepancy.

A suitable choice for K is returned.

To Duc, K., Chiogna, M., Adimari, G. (2016): Nonparametric Estimation of ROC Surfaces Under Verification Bias. https://arxiv.org/abs/1604.04656v1. Submitted.

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