eclairs-class: Class eclairs

In GabrielHoffman/mvIC: Multivariate Information Criteria to identify important predictors in high dimensional multivariate regression

Class eclairs

Description

Class eclairs

Details

Object storing:

• U: orthonormal matrix with k columns representing the low rank component

• dSq: eigen-values so that U diag(d^2) U^T is the low rank component

• lambda: shrinkage parameter λ for the scaled diagonal component

• nu: diagonal value, ν, of target matrix in shrinkage

• n: number of samples (i.e. rows) in the original data

• p: number of features (i.e. columns) in the original data

• k: rank of low rank component

• rownames: sample names from the original matrix

• colnames: features names from the original matrix

• method: method used for decomposition

• call: the function call

GabrielHoffman/mvIC documentation built on Aug. 30, 2022, 7:58 p.m.