Sparse Group Partial Least Square Methods

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Documentation for package ‘sgPLS’ version 1.2

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sgPLS-package Group and Sparse Group Partial Least Square Model
gPLS Group Partial Least Squares (gPLS)
lambda.quadra Internal Functions
normv Internal Functions
per.variance Percentage of variance of the Y matrix explained by the score-vectors obtained by PLS approaches
perf Compute evaluation criteria for PLS, sPLS, PLS-DA and sPLS-DA
perf.gPLS Compute evaluation criteria for PLS, sPLS, PLS-DA and sPLS-DA
perf.sgPLS Compute evaluation criteria for PLS, sPLS, PLS-DA and sPLS-DA
perf.sPLS Compute evaluation criteria for PLS, sPLS, PLS-DA and sPLS-DA
plotcim Plots a cluster image mapping of correlations between outcomes and all predictors
predict.gPLS Predict Method for sPLS, gPLS or sgPLS
predict.sgPLS Predict Method for sPLS, gPLS or sgPLS
predict.sPLS Predict Method for sPLS, gPLS or sgPLS
select.sgpls Output of selected variables from a gPLS model or a sgPLS model
select.spls Output of selected variables from a sPLS model
sgPLS Sparse Group Partial Least Squares (sgPLS)
soft.thresholding Internal Functions
soft.thresholding.group Internal Functions
soft.thresholding.sparse.group Internal Functions
sPLS Sparse Partial Least Squares (sPLS)
step1.group.spls.sparsity Internal Functions
step1.sparse.group.spls.sparsity Internal Functions
step1.spls.sparsity Internal Functions
step2.spls Internal Functions
tuning.gPLS.X Choice of the tuning parameter (number of groups) related to predictor matrix for gPLS model (regression mode)
tuning.sgPLS.X Choice of the tuning parameters (number of groups and mixing parameter) related to predictor matrix for sgPLS model (regression mode)
tuning.sPLS.X Choice of the tuning parameter (number of variables) related to predictor matrix for sPLS model (regression mode)