vip {integrOmics}R Documentation

Variable Importance in the Projection (VIP)

Description

The function vip computes the influence on the Y-responses of every predictor X in the model.

Usage

vip(object)

Arguments

object object of class inheriting from "pls" or "spls".

Details

Variable importance in projection (VIP) coefficients reflect the relative importance of each X variable for each X variate in the prediction model. VIP coefficients thus represent the importance of each X variable in fitting both the X- and Y-variates, since the Y-variates are predicted from the X-variates.

VIP allows to classify the X-variables according to their explanatory power of Y. Predictors with large VIP, larger than 1, are the most relevant for explaining Y.

Value

vip produces a matrix of VIP coefficients for each X variable (rows) on each variate component (columns).

Author(s)

Sébastien Déjean and Ignacio González.

References

Tenenhaus, M. (1998). La régression PLS: théorie et pratique. Paris: Editions Technic.

See Also

pls, pls, summary.

Examples

data(linnerud)
X <- linnerud$exercise
Y <- linnerud$physiological
linn.pls <- pls(X, Y)

linn.vip <- vip(linn.pls)

barplot(linn.vip,
        beside = TRUE, col = c("lightblue", "mistyrose", "lightcyan"),
        ylim = c(0, 1.7), legend = rownames(linn.vip),
        main = "Variable Importance in the Projection", font.main = 4)

[Package integrOmics version 2.5 Index]