Function to aggregate positions defined via indirect relations to construct centrality scores.
Numeric matrix containing indirect relations calculated with indirect_relations.
String indicating the type of aggregation to be used. See Details for options.
The predefined functions are mainly wrappers around base R functions.
type='sum', for instance, is equivalent to
rowSums(). A non-base functions is
type='invsum' which calculates the inverse of type='sum'.
type='self' is mostly useful for walk based relations, e.g. to count closed walks.
Other self explanatory options are type='mean', type='min', type='max' and type='prod'.
Scores for the index defined by the indirect relation
tau_x and the
used aggregation type.
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library(igraph) library(magrittr) g <- graph.empty(n=11,directed = FALSE) g <- add_edges(g,c(1,11,2,4,3,5,3,11,4,8,5,9,5,11,6,7,6,8, 6,10,6,11,7,9,7,10,7,11,8,9,8,10,9,10)) #degree g %>% indirect_relations(type='adjacency') %>% aggregate_positions(type='sum') #closeness centrality g %>% indirect_relations(type='dist_sp') %>% aggregate_positions(type='invsum') #betweenness centrality g %>% indirect_relations(type='depend_sp') %>% aggregate_positions(type='sum') #eigenvector centrality g %>% indirect_relations(type='walks',FUN=walks_limit_prop) %>% aggregate_positions(type='sum') #subgraph centrality g %>% indirect_relations(type='walks',FUN=walks_exp) %>% aggregate_positions(type='self')
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