fastHICA (version 1.0.2)

similarity_hica: Estimate of the similarity matrix

Description

This function provides an estimate of the similarity matrix of the original data, before performing HICA algorithm.

Usage

similarity_hica(X, dim.subset = 512)

Arguments

X

Data matrix with nrow(X) observations and ncol(X) variables.

dim.subset

The dimension of the subset used for the evaluation of the similarity index (i.e., distance correlation). If this it is greater than nrow(X) all the observations are used, unless a random subset of dim.subset observations is used. The default value is set to 512.

Value

similarity_matrix

similarity matrix of the original data.

subset

subset used for the evaluation of distance correlation between variables.

Details

This function is auxiliary for the basis_hica function. Indeed its output is the estimate of the similarity matrix at the first step of the algorithm.

References

P. Secchi, S. Vantini, and P. Zanini (2014). Hierarchical Independent Component Analysis: a multi-resolution non-orthogonal data-driven basis. MOX-report 01/2014, Politecnico di Milano.

See Also

basis_hica, energy_hica, extract_hica