print produces an output for objects of class origin.

# S3 method for origin
print(x, ...)

# S3 method for origin
summary(object, x = object, ...)

# S3 method for origin
plot(x, y = "id", start, ...)

# S3 method for origin
performance(x, start, graph = NULL, ...)

Arguments

x

object of class origin, origin estimation object from function origin_xxx

...

further arguments to be passed to default plot function

object

object of class origin, origin estimation object from function origin_xxx; passed to x

y

character specifying the variable being plotted at the y-axis; options are 'id' for node identifier (default), 'mdist' for mean distance (only available for origin_edm) or 'wvar' for weighted variance (only available for origin_edm)

start

numeric, giving the node of the true origin

graph

igraph object specifying the underlying network graph with attribute 'length' on edges for calculation of distance to the correct origin

Value

performance.origin returns a data.frame with variables

  • origin = start representing the true origin,

  • est the estimated node of origin,

  • hitt logical indicating whether origin estimation is correct or not,

  • rank rank of correct detection,

  • spj number of segments from estimated origin to true origin (requires an igraph object),

  • dist distance along the shortest path from estimated origin to true origin (igraph edge attribute length)

See also

Examples

data(ptnGoe) data(delayGoe) res <- origin(events=delayGoe[10,-c(1:2)], type='centrality', graph=ptnGoe) res
#> Centrality-based origin estimation: #> #> estimated node of origin 119: X.Hermann.Kolbe.Strasse
summary(res)
#> Centrality-based origin estimation: #> #> estimated node of origin 119: X.Hermann.Kolbe.Strasse #> #> auxiliary variables: #> id events cent #> Min. : 1 Min. : 0.0000 Min. :0.000 #> 1st Qu.: 65 1st Qu.: 0.0000 1st Qu.:2.938 #> Median :129 Median : 0.0000 Median :5.875 #> Mean :129 Mean : 0.6459 Mean :5.167 #> 3rd Qu.:193 3rd Qu.: 0.0000 3rd Qu.:8.062 #> Max. :257 Max. :46.0000 Max. :9.000 #> NA's :247
plot(res, start=1)
performance(res, start=1, graph=ptnGoe)
#> start est hitt rank spj dist #> 1 X.Adolf.Hoyer.Strasse X.Hermann.Kolbe.Strasse FALSE 9 5 3330