vip: Variable Importance in the Projection (VIP)

In ajabadi/mixOmics2: Omics Data Integration Project

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", "plsda", "spls" or "splsda".

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 Gonz\'alez.

References

Tenenhaus, M. (1998). La regression PLS: theorie et pratique. Paris: Editions Technic.

See Also

pls, spls, summary.

Examples

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)

ajabadi/mixOmics2 documentation built on Aug. 9, 2019, 1:08 a.m.