explained_variance: Calculation of explained variance

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/explained_variance.R

Description

This function calculates the variance explained by their own variates (components) based on redundancy.

Usage

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explained_variance(data, variates, ncomp)

Arguments

data

numeric matrix of predictors

variates

variates as obtained from a pls object for instance

ncomp

number of components. Should be lower than the number of columns of variates

Details

explained_variance calculates the variance explained by each variate / component and divides by the total variance in data using the definition of 'redundancy'. This applies to any component-based approaches.

Variance explained by component t_h in X for dimension h:

Rd(X, t_h) = \frac{1}{p} ∑_{j = 1}^p \mbox{cor}^2(X^j, t_h)

where X^j is the variable centered and scaled, p is the total number of variables.

Value

explained_variance returns the explained variance for each variate.

Author(s)

Florian Rohart, Kim-Anh Lê Cao, Al J Abadi

References

Tenenhaus, M., La Régression PLS théorie et pratique (1998). Technip, Paris, chap2.

See Also

spls, splsda, plotIndiv, plotVar, cim, network.

Examples

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data(liver.toxicity)
X <- liver.toxicity$gene
Y <- liver.toxicity$clinic

toxicity.spls <- spls(X, Y, ncomp = 2, keepX = c(50, 50), keepY = c(10, 10))

ex = explained_variance(toxicity.spls$X, toxicity.spls$variates$X, ncomp =2)

# ex should be the same as
toxicity.spls$explained_variance$X

mixOmics documentation built on Nov. 8, 2020, 11:12 p.m.