Description Usage Arguments Details Value Author(s) See Also Examples

View source: R/aggregate.index.R

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

1 | ```
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

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 | ```
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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