Description Usage Arguments Details Value References Examples
View source: R/complexity_measures.R
complexity_measures()
computes different complexity
measures obtained from the Balassa Index or a binary (0/1) metric for a
bipartite relation between two disjoint sets X, the "source" or "from" side,
and Y, the "target" or "to" side.
1 2 | complexity_measures(balassa_index, method = "fitness", iterations = 20,
extremality = 1)
|
balassa_index |
(Type: matrix or dgCMatrix) the output from
|
method |
(Type: character) one of these methods: fitness,
reflections or eigenvalues. By default this is set to |
iterations |
(Type: numeric) the number of iterations to use.
By default this is set to |
extremality |
(Type: numeric) the parameter to use in the fitness
method. The other methods don't use this parameter.
By default this is set to |
The current implementation follows \insertCitemeasuringcomplexity2015binet to obtain different metrics that account for diversification in bipartite relations.
A list of four data frames. Two complexity indexes that are ordering rankings for specialization and two aggregations (sums) of the Balassa Index.
For more information on this index see:
\insertRefmeasuringcomplexity2015binet
and the references therein.
1 |
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