R: Resolve the splitMethod for estimation of prediction...

resolvesplitMethod {pec} | R Documentation

## Resolve the splitMethod for estimation of prediction performance

### Description

The function computes a matrix of random indices obtained by drawing from the row numbers of a data set either with or without replacement. The matrix can be used to repeatedly set up independent training and validation sets.

### Usage

    resolvesplitMethod(splitMethod, B, N, M)

### Arguments

`splitMethod` | String that determines the splitMethod to use. Available splitMethods are none/noPlan (no splitting), bootcv or outofbag (bootstrap cross-validation), cvK (K-fold cross-validation, e.g. cv10 gives 10-fold), boot632, boot632plus or boot632+, loocv (leave-one-out)
`B` | The number of repetitions.
`N` | The sample size
`M` | For subsampling bootstrap the size of the subsample. Note M<N.

### Value

A list with the following components

`name` | the official name of the splitMethod
`internal.name` | the internal name of the splitMethod
`index` | a matrix of indices with B columns and either N or M rows, dependent on splitMethod
`B` | the value of the argument B
`N` | the value of the argument N
`M` | the value of the argument M

### Author(s)

Thomas Alexander Gerds tag@biostat.ku.dk

### Examples

      # BootstrapCrossValidation: Sampling with replacement
      resolvesplitMethod("BootCv",N=10,B=10)

      # 10-fold cross-validation: repeated 2 times
      resolvesplitMethod("cv10",N=10,B=2)

      # leave-one-out cross-validation
      resolvesplitMethod("loocv",N=10)

      resolvesplitMethod("bootcv632plus",N=10,B=2)

[Package pec version 2022.03.06 Index]