boot_ttest: Bootstrap univariate filters

In nestedcv: Nested Cross-Validation with 'glmnet' and 'caret'

Bootstrap univariate filters

Description

Randomly samples predictors and averages the ranking from filtering functions including ttest_filter(), wilcoxon_filter(), anova_filter(), correl_filter() and lm_filter() to give an ensemble measure of best predictors by repeated random sampling subjected to a statistical test.

Usage

boot_ttest(y, x, B = 50, ...)

boot_wilcoxon(y, x, B = 50, ...)

boot_anova(y, x, B = 50, ...)

boot_correl(y, x, B = 50, ...)

boot_lm(y, x, B = 50, ...)

Arguments

y	Response vector
x	Matrix of predictors
B	Number of times to bootstrap
...	Optional arguments passed to the filter function

Value

Integer vector of indices of filtered parameters (type = "index"), or if type = "full", a matrix of rankings from each bootstrap is returned.

See Also

ttest_filter(), wilcoxon_filter(), anova_filter(), correl_filter(), lm_filter() and boot_filter()

nestedcv documentation built on April 4, 2025, 2:21 a.m.