aggregate_positions: Quantification of (indirect) relations

In netrankr: Analyzing Partial Rankings in Networks

Quantification of (indirect) relations

Description

Function to aggregate positions defined via indirect relations to construct centrality scores.

Usage

aggregate_positions(tau_x, type = "sum")

Arguments

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.

Details

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'.

Value

Scores for the index defined by the indirect relation tau_x and the used aggregation type.

Author(s)

David Schoch

See Also

indirect_relations, transform_relations

Examples

library(igraph)
library(magrittr)

data("dbces11")
# degree
dbces11 %>%
  indirect_relations(type = "adjacency") %>%
  aggregate_positions(type = "sum")

# closeness centrality
dbces11 %>%
  indirect_relations(type = "dist_sp") %>%
  aggregate_positions(type = "invsum")

# betweenness centrality
dbces11 %>%
  indirect_relations(type = "depend_sp") %>%
  aggregate_positions(type = "sum")

# eigenvector centrality
dbces11 %>%
  indirect_relations(type = "walks", FUN = walks_limit_prop) %>%
  aggregate_positions(type = "sum")

# subgraph centrality
dbces11 %>%
  indirect_relations(type = "walks", FUN = walks_exp) %>%
  aggregate_positions(type = "self")

netrankr documentation built on Aug. 20, 2023, 5:06 p.m.