ConsensusOPLS-class: 'ConsensusOPLS' S4 class

In ConsensusOPLS: Consensus OPLS for Multi-Block Data Fusion

ConsensusOPLS S4 class

Description

An object returned by the ConsensusOPLS function, of class ConsensusOPLS, and representing a fitted Consensus OPLS model.

Slots

modelType

The type of requested OPLS regression model.

response

The provided response variable (Y).

nPcomp

Number of Y-predictive components (latent variables) of the optimal model.

nOcomp

Number of Y-orthogonal components (latent variables) of the optimal model.

blockContribution

Relative contribution of each block (normalized lambda values) to the latent variables.

scores

Representation of the samples in the latent variables of the optimal model.

loadings

Contribution of each block's variables to the latent variables of the optimal model.

VIP

Variable importance in projection (VIP) for each block of data, assessing the relevance of the variables in explaining the variation in the response.

R2X

Proportion of variation in data blocks explained by the optimal model.

R2Y

Proportion of variation in the response explained by the optimal model.

Q2

Predictive ability of the optimal model.

DQ2

Predictive ability of the optimal discriminant model.

permStats

Assessment of models with permuted response.

model

The optimal model.

cv

Cross-validation result towards the optimal model. Contains AllYhat (all predicted Y values as a concatenated matrix), cvTestIndex (indexes for the test set observations during the cross-validation rounds), DQ2Yhat (total discriminant Q-square result for all Y-orthogonal components), nOcompOpt (optimal number of Y-orthogonal components (latent variables) for the optimal model), and Q2Yhat (total Q-square result for all Y-orthogonal components).

ConsensusOPLS documentation built on April 3, 2025, 11:16 p.m.