# local_scan

##### Compute local scan statistics on graphs

The scan statistic is a summary of the locality statistics that is
computed from the local neighborhood of each vertex. The
`local_scan`

function computes the local statistics for each vertex
for a given neighborhood size and the statistic function.

##### Usage

```
local_scan(graph.us, graph.them = NULL, k = 1, FUN = NULL,
weighted = FALSE, mode = c("out", "in", "all"), neighborhoods = NULL,
...)
```

##### Arguments

- graph.us,graph
- An igraph object, the graph for which the scan statistics will be computed
- graph.them
- An igraph object or
`NULL`

, if not`NULL`

, then thethem statistics is computed, i.e. the neighborhoods calculated from`graph.us`

are evaluated on`graph.them`

. - k
- An integer scalar, the size of the local neighborhood for each vertex. Should be non-negative.
- FUN
- Character, a function name, or a function object itself, for
computing the local statistic in each neighborhood. If
`NULL`

(the default value),`ecount`

is used for unweighted graphs (if`weighted=FALSE`

) and a function tha - weighted
- Logical scalar, TRUE if the edge weights should be used
for computation of the scan statistic. If TRUE, the graph should be
weighted. Note that this argument is ignored if
`FUN`

is not`NULL`

,`"ecount"`

and`"sumwei`

- mode
- Character scalar, the kind of neighborhoods to use for the
calculation. One of
,`out`

,`in`

or`all`

. This argument is ignored for undi`total`

- neighborhoods
- A list of neighborhoods, one for each vertex, or
`NULL`

. If it is not`NULL`

, then the function is evaluated on the induced subgraphs specified by these neighborhoods.In theory this could be useful if the same

`graph.us<`

- ...
- Arguments passed to
`FUN`

, the function that computes the local statistics.

##### Details

See the given reference below for the details on the local scan statistics.

`local_scan`

calculates exact local scan statistics.

If `graph.them`

is `NULL`

, then `local_scan`

computes the
`graph.them`

should be an igraph object and the `graph.us`

to extract the neighborhood
information, and applying `FUN`

on these neighborhoods in
`graph.them`

.

##### Value

- For
`local_scan`

typically a numeric vector containing the computed local statistics for each vertex. In general a list or vector of objects, as returned by`FUN`

.

##### References

Priebe, C. E., Conroy, J. M., Marchette, D. J., Park,
Y. (2005). Scan Statistics on Enron Graphs. *Computational and
Mathematical Organization Theory*.

##### See Also

Other scan statistics: `scan_stat`

##### Examples

```
pair <- sample_correlated_gnp_pair(n = 10^3, corr = 0.8, p = 0.1)
local_0_us <- local_scan(graph.us = pair$graph1, k = 0)
local_1_us <- local_scan(graph.us = pair$graph1, k = 1)
local_0_them <- local_scan(graph.us = pair$graph1,
graph.them = pair$graph2, k = 0)
local_1_them <- local_scan(graph.us = pair$graph1,
graph.them = pair$graph2, k = 1)
Neigh_1 <- neighborhood(pair$graph1, order = 1)
local_1_them_nhood <- local_scan(graph.us = pair$graph1,
graph.them = pair$graph2,
neighborhoods = Neigh_1)
```

*Documentation reproduced from package igraph, version 1.0.0, License: GPL (>= 2)*