depna: Dependency Neural Networks

Description Usage Arguments Value Author(s) References Examples

Description

Applies the dependency network approach to neural network array

Usage

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depna(neuralarray, cores, ...)

Arguments

neuralarray

Array from convertConnBrainMat function

cores

Numeric. Number of cores to use in computing results. Set to 1 to not use parallel computing. Recommended to use maximum number of cores minus one

...

Additional arguments from depend function

Value

Returns an array of n x n x m dependency matrices

Author(s)

Alexander Christensen <alexpaulchristensen@gmail.com>

References

Jacob, Y., Winetraub, Y., Raz, G., Ben-Simon, E., Okon-Singer, H., Rosenberg-Katz, K., ... & Ben-Jacob, E. (2016). Dependency Network Analysis (DEPNA) reveals context related influence of brain network nodes. Scientific Reports, 6, 27444.

Kenett, D. Y., Tumminello, M., Madi, A., Gur-Gershgoren, G., Mantegna, R. N., & Ben-Jacob, E. (2010). Dominating clasp of the financial sector revealed by partial correlation analysis of the stock market. PLoS one, 5, e15032.

Examples

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## Not run: 
neuralarray <- convertConnBrainMat()

dependencyneuralarray <- depna(neuralarray)

## End(Not run)

NetworkToolbox documentation built on May 28, 2021, 5:11 p.m.