concept.indices {FCMapper}

Concept indices

Description

Concept-level indices are calculated, including the out-degree, in-degree, centrality, and whether it is a transmitter, reveiver, ordinary or unconnected concept.

Usage

concept.indices(matrix, concept.names)

Arguments

matrix

A quantitative fuzzy cognitive map.

concept.names

A character vector.

Details

The fuzzy cognitive map should be in the form of a quantitative adjacency matrix. The concept.names input is the names of the concepts in the fuzzy cognitive map.

Value

A dataframe containing the concept name, out-degree, in-degree, centrality, and whether it is a transmitter, reveiver, ordinary or unconnected concept.

Author(s)

Shaun Turney

Examples

matrix = matrix(nrow=7,ncol=7)
matrix[1,] = c(0,-0.5,0,0,1,0,1)
matrix[2,] = c(1,0,1,0.2,0,0,0.6)
matrix[3,] = c(0,1,0,0,0,0,0)
matrix[4,] = c(0.6,0,0,1,0,0,0.1)
matrix[5,] = c(0,0.5,0,0,1,0,-0.6) 
matrix[6,] = c(0,0,-1,0,0,0,0)
matrix[7,] = c(0,0,0,-0.5,0,0,1)
concept.names = c("A","B","C","D","E","F","G")

concept.indices(matrix,concept.names)