# transitivity: calculate transitivity measurements for a matrix In Perc: Using Percolation and Conductance to Find Information Flow Certainty in a Direct Network

## Description

transitivity calculate transitivity measurements for a matrix

## Usage

 1 transitivity(conf, strict = FALSE)

## Arguments

 conf an N-by-N conflict matrix whose (i,j)th element is the number of times i defeated j strict a logical vector of length 1 (TRUE or FALSE). It is used in transitivity definition for alpha estimation. It should be set to TRUE when a transitive triangle is defined as all pathways in the triangle go to the same direction; it should be set to FALSE when a transitive triangle is defined as PRIMARY pathways in the triangle go to the same direction. Strict = FALSE by default.

## Details

transitivity is calculated as the proportion transitive triangles in the total of transitive and intransitive triangles. transitivity is used to estimate alpha, which is used in turn in imputing information from indirect pathways as to what degree we can trust information from indirect pathways. Greater transitivity is associated with assigning higher weight to information from indirect pathways.

## Value

A list of four elements.

 transitive The number of transitive triangles. intransitive The number of intransitive triangles. transitivity transitivity, the proportion of transitive triangles. alpha The value of alpha corresponding to this value of transitivity.

## Examples

 1 2 3 4 5 6 7 8 # convert an edgelist to conflict matrix confmatrix <- as.conflictmat(sampleEdgelist) # transitivity calculation conftrans <- transitivity(confmatrix, strict = FALSE) conftrans\$transitive conftrans\$intransitive conftrans\$transitivity conftrans\$alpha

### Example output

[1] 14
[1] 4
[1] 0.7777778
[1] 6.468627

Perc documentation built on April 28, 2020, 1:08 a.m.