Thresholded Ordered Sparse CCA

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Documentation for package ‘toscca’ version 0.1.0

• DESCRIPTION file.
• User guides, package vignettes and other documentation.

Help Pages

cpev.toscca	Calculates cpev
fastEigen	Performs eigen decomposition of a matrix in PS space.
getCanSubspace	Performs matrix residualisation over estimated canonical vectors by using the null space of the estimated canonical vector to construct a new matrix.
getWhich	Get location of required.
initialiseCanVar	Initialised the canonical vector for the iterative process based on positive eigen values. Then, SVD is performed on that PS matrix.
modes	Calculates mode.
myHeatmap	Plot heatmap of cv w.r.t. the penalty parameter perfotmance.
plt.selstab	Plot slection stability for penalty parameter performance.
powerMethod	Performs power method.
progressBar	Progress bar
residualisation	Performs matrix residualisation over estimated canonical vectors. There are three types: basic (subtracts scaled estimated latent variable from data), null (uses the null space of the estimated canonical vector to construct a new matrix) and LV (uses SVD to residualise).
scaledResidualMat	Performs scalling for matrix residualisation based on calculated coefficients.
scale_rm	Standardises matrices with multiple measurements per individual.
standardVar	Stardardise a matrix
toscamm.perm	Computes permutatied cc fot TOSCCA-MM
toscca	Sparse Canonical Correlation Analysis. Computation of CC via NIPALS with soft thresholding.
toscca.core	Sparse Canonical Correlation Analysis. Computation of CC via NIPALS with soft thresholding.
toscca.folds	Sparse Canonical Correlation Analysis. Computation of CC via NIPALS with soft thresholding.
toscca.lv	Get latent variables
toscca.perm	Permutation testing for toscca
toscca.tStat	Get the estatistic for the permutations.
tosccamm	Computes TOSCCA-MM