View source: R/relatedness_density_int.r
relatedness_density_int | R Documentation |
This function computes the relatedness density between regions and industries that are part of the regional portfolio from regions - industries (incidence) matrices and industries - industries (adjacency) matrices
relatedness_density_int(mat, relatedness)
mat |
An incidence matrix with regions in rows and industries in columns |
relatedness |
An adjacency industry - industry matrix indicating the degree of relatedness between industries |
A matrix representing the relatedness density between regions and industries that are part of the regional portfolio. The values in the matrix indicate the relatedness density for each region and industry, scaled from 0 to 100.
Pierre-Alexandre Balland p.balland@uu.nl
Boschma, R., Balland, P.A. and Kogler, D. (2015) Relatedness and Technological Change in Cities: The rise and fall of technological knowledge in U.S. metropolitan areas from 1981 to 2010, Industrial and Corporate Change 24 (1): 223-250
Boschma, R., Heimeriks, G. and Balland, P.A. (2014) Scientific Knowledge Dynamics and Relatedness in Bio-Tech Cities, Research Policy 43 (1): 107-114
relatedness
, co_occurrence
## generate a region - industry matrix in which cells represent the presence/absence
## of a RCA
set.seed(31)
mat <- matrix(sample(0:1, 20, replace = TRUE), ncol = 4)
rownames(mat) <- c("R1", "R2", "R3", "R4", "R5")
colnames(mat) <- c("I1", "I2", "I3", "I4")
## generate an industry - industry matrix in which cells indicate if two industries are
## related (1) or not (0)
relatedness <- matrix(sample(0:1, 16, replace = TRUE), ncol = 4)
relatedness[lower.tri(relatedness, diag = TRUE)] <- t(relatedness)[lower.tri(t(relatedness),
diag = TRUE
)]
rownames(relatedness) <- c("I1", "I2", "I3", "I4")
colnames(relatedness) <- c("I1", "I2", "I3", "I4")
## run the function
relatedness_density_int(mat, relatedness)
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