modular.complexity: Compute a measure of modular complexity of patent documents

In PABalland/EconGeo: Computing Key Indicators of the Spatial Distribution of Economic Activities

Compute a measure of modular complexity of patent documents

Description

This function computes a measure of modular complexity of patent documents from technological classes - patents (incidence) matrices

Usage

modular.complexity(mat, sparse = FALSE, list = FALSE)

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 [e-mail]

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

## 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 (mat)

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

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

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

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

PABalland/EconGeo documentation built on Jan. 5, 2023, 8:40 a.m.