depna: Dependency Neural Networks

Description Usage Arguments Value Author(s) References Examples

View source: R/NetworkToolbox--master.R

Description

Applies the dependency network approach to neural network array

Usage

1
depna(neuralarray, pB = TRUE, ...)

Arguments

neuralarray

Array from convertConnBrainMat function

pB

Should progress bar be displayed? Defaults to TRUE. Set FALSE for no progress bar

...

Additional arguments from depend function

Value

Returns an array of n x n x m dependency matrices

Author(s)

Alexander Christensen <[email protected]>

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(12), e15032.

Examples

1
2
3
4
5
6
## Not run: 
neuralarray <- convertConnBrainMat()

dependencyneuralarray <- depna(neuralarray)

## End(Not run)

AlexChristensen/NetworkToolbox documentation built on May 6, 2018, 7:39 p.m.