nodal.network: Computes nodal spanners

Description Usage Arguments Details Value Examples

Description

Computes whether an individual spans (has connections in) another niche and the number of other niches each individual spans to.

Usage

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nodal.network(blauObj, dev.range, ecologies.off = FALSE)

Arguments

blauObj

An object of class blau initialized with the function blau. Individuals will automatically be placed in niches with the function niches if this has not been done manually.

dev.range

When creating niches, indicates standard deviation around the mean in each dimension to include in niche. A larger value will make niches larger and therefore include more individuals.

ecologies.off

Defaults to FALSE. If set to TRUE, treats all individuals as in the same ecology, even if ecology identifiers (ecology.ids) have been specified. Will call the niches function and overwrite its output even if it has been manually called by the user.

Details

This function requires sociometric network data and identifies ties that bridge niches. The preferred format is a named edgelist, although an adjacency matrix with properly named rows and columns is also acceptable. Network information will be matched to organization and demographic information by these names.

For individuals i and j in niches alpha and beta, if individual i is in niche alpha and individual j is in niche beta, and i and j have an edge between them, then i spans to niche beta and j spans to niche alpha. However, if i is in both niche alpha and niche beta, i would not span to beta because i is already in niche beta.

Value

A matrix stored in object$nodalNetwork with two columns holding the two measures. Row names are node names provided with the blau function.

Examples

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data(BSANet)
el <- BSANet$el
square.data <- BSANet$square.data
b <- blau(square.data, node.ids = 'person', ecology.ids = 'city', graph = el)
#will automatically compute niches
b <- nodal.network(b, dev.range = rep(1.5, 3)) # 3 is the number of dimensions

Blaunet documentation built on May 1, 2019, 8:21 p.m.