modular.complexity.avg: Compute a measure of average modular complexity of...

Description Usage Arguments Author(s) References See Also Examples

View source: R/modular.complexity.avg.r

Description

This function computes a measure of average modular complexity of technologies (average complexity of patent documents in a given technological class) from technological classes - patents (incidence) matrices

Usage

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Arguments

mat

A bipartite adjacency matrix (can be a sparse matrix)

sparse

Logical; is the input matrix a sparse matrix? Defaults to FALSE, but can be set to TRUE if the input matrix is a sparse matrix

list

Logical; is the input a list? Defaults to FALSE (input = adjacency matrix), but can be set to TRUE if the input is an edge list

Author(s)

Pierre-Alexandre Balland p.balland@uu.nl

References

Fleming, L. and Sorenson, O. (2001) Technology as a complex adaptive system: evidence from patent data, Research Policy 30: 1019-1039

See Also

ease.recombination, TCI, MORt

Examples

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## generate a technology - patent matrix
set.seed(31)
mat <- matrix(sample(0:1,30,replace=T), ncol = 5)
rownames(mat) <- c ("T1", "T2", "T3", "T4", "T5", "T6")
colnames(mat) <- c ("US1", "US2", "US3", "US4", "US5")

## run the function
modular.complexity.avg (mat)

## generate a technology - patent sparse matrix
library (Matrix)

## run the function
smat <- Matrix(mat,sparse=TRUE)

modular.complexity.avg (smat, sparse = TRUE)
## generate a regular data frame (list)
list <- get.list (mat)

## run the function
modular.complexity.avg (list, list = TRUE)

PABalland/EconGeo documentation built on Nov. 13, 2020, 2:50 a.m.