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. |

Scores for the index defined by the indirect relation `tau_x`

and the
used aggregation type.

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'.

indirect_relations, transform_relations

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='identity') %>% aggregate_positions(type='sum')#> Warning: type="identity" is deprecated. Using "adjacency" instead.#> [1] 1 1 2 2 3 4 4 4 4 4 5#closeness centrality g %>% indirect_relations(type='dist_sp') %>% aggregate_positions(type='invsum')#> [1] 0.03704 0.02941 0.04000 0.04000 0.05000 0.05882 0.05263 0.05556 0.05556 #> [10] 0.05263 0.05556#betweenness centrality g %>% indirect_relations(type='depend_sp') %>% aggregate_positions(type='sum')#> [1] 0.000 0.000 0.000 18.000 7.667 19.667 5.333 32.667 14.667 2.667 #> [11] 29.333#eigenvector centrality g %>% indirect_relations(type='walks',FUN=walks_limit_prop) %>% aggregate_positions(type='sum')#> [1] 0.27516 0.07864 0.46106 0.29410 0.69521 1.19904 1.21772 1.02121 1.10978 #> [10] 1.21608 1.02901#subgraph centrality g %>% indirect_relations(type='walks',FUN=walks_exp) %>% aggregate_positions(type='self')#> [1] 1.825 1.595 3.149 2.423 4.387 7.807 7.939 6.673 7.033 8.242 7.390