initializations: Computes number of initializations to be performed by ica_pca

Description Usage Arguments Details Value Author(s) Examples

Description

For a given number of sub-Gaussian and super-Gaussian sources and Gaussian components, the function ica_pca will initialize the model multiple times. This function will compute the number of initializations that will be performed.

Usage

1
initializations(subgaussians, supergaussians, gaussians)

Arguments

subgaussians

the number of sub-Gaussian sources in the model

supergaussians

the number of super-Gaussian sources in the model

gaussians

the number of Gaussian sources in the model

Details

If the number of initializations is small (less than 50 to 100), the ica_pca function may fail to identify the optimal model; models with small numbers of initializations should be run several times using different values for seed and/or offset_random. As the number of sources and components gets large (e.g., with totals more than 10) the number of initializations grows quickly. To a first approximation, computation time is proportional to the number of initializations.

Value

returns the number of initializations

Author(s)

Roger P. Woods, M.D.

Examples

1

icapca documentation built on May 2, 2019, 12:57 a.m.