bootstrap: Bootstrap resampling

In computational-metabolomics/structToolbox: Data processing & analysis tools for Metabolomics and other omics

Bootstrap resampling

Description

In bootstrap resampling a subset of samples is selected at random with replacement to form a training set. Any sample not selected for training is included in the test set. This process is repeated many times, and performance metrics are computed for each repetition.

Usage

bootstrap(number_of_repetitions = 100, collect, ...)

Arguments

number_of_repetitions	(numeric, integer) The number of bootstrap repetitions. The default is 100.
collect	(character) The name of a model output to collect over all bootstrap repetitions, in addition to the input metric.
...	Additional slots and values passed to struct_class.

Value

A bootstrap object with the following output slots:

results	(data.frame)
metric	(data.frame)
collected	(logical, list)

Inheritance

A bootstrap object inherits the following struct classes:

⁠[bootstrap]⁠ >> ⁠[resampler]⁠ >> ⁠[iterator]⁠ >> ⁠[struct_class]⁠

Examples

M = bootstrap(
      number_of_repetitions = 10,
      collect = "vip")

I = bootstrap(number_of_repetitions = 10, collect = 'vip')

computational-metabolomics/structToolbox documentation built on Feb. 12, 2024, 2:15 a.m.