scoreTest {powerPLS}

Score test

Description

Performs randomization test based on predictive score vector

Usage

scoreTest(X, Y, nperm = 100, A, randomization = FALSE, Y.prob = FALSE, eps = 0.01,...)

Arguments

X

data matrix where columns represent the p variables and rows the n observations.

Y

data matrix where columns represent the two classes and rows the n observations.

nperm

number of permutations. Default 100.

A

number of score components

randomization

Boolean value. Default @FALSE. If @TRUE the permutation p-value is computed

Y.prob

Boolean value. Default @FALSE. IF @TRUE Y is a probability vector

eps

Default 0.01. eps is used when Y.prob = FALSE to transform Y in a probability vector

...

Further parameters.

Value

Returns a list with the corresponding statistical tests, raw and adjusted p-values

List with the following objects: pv: raw p-value, pv_adj: adjusted p-value, test estimated statistical test.

Author(s)

Angela Andreella

References

For the general framework of power analysis for PLS-based methods see:

See Also

The type of tests implemented: mccTest R2Test.

Examples

datas <- simulatePilotData(nvar = 30, clus.size = c(5,5),m = 6,nvar_rel = 5,A = 2)
out <- scoreTest(X = datas$X, Y = datas$Y, A = 1)
out