modular_complexity {EconGeo}

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

Value

A data frame with columns "patent" and "mod.comp" representing the patents and their corresponding modular complexity values.

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 = TRUE), 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)
my_list <- get_list(mat)

## run the function
modular_complexity(my_list, list = TRUE)