View source: R/modular.complexity.avg.r
modular.complexity.avg | R Documentation |
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
modular.complexity.avg(mat, sparse = FALSE, list = FALSE)
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 |
Pierre-Alexandre Balland p.balland@uu.nl
Fleming, L. and Sorenson, O. (2001) Technology as a complex adaptive system: evidence from patent data, Research Policy 30: 1019-1039
ease.recombination
, TCI
, MORt
## 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)
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