View source: R/aggregate.index.R

aggregate_positions | R Documentation |

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

indirect_relations, transform_relations

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")

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