explained_variance: Calculation of explained variance
In mixOmics: Omics Data Integration Project

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

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

1	explained_variance(data, variates, ncomp)

`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`

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.

explained_variance returns the explained variance for each variate.

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

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

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

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