Quantification of (indirect) relations
Function to aggregate positions defined via indirect relations to construct centrality scores.
aggregate_positions(tau_x, type = "sum")
tau_x |
Numeric matrix containing indirect relations calculated with indirect_relations. |
type |
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.
David Schoch
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')Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.