conpowerlaw.stat: Continuous Power-Law Scan Statistic

In taichi43/SNscan: Scan Statistics in Social Networks

Description

The continuous power law scan statistic evaluate the statistic which compare the node attribute within the subgraph with that outside the subgraph while the node attribute follows the continuous power-law distribution.

Usage

conpowerlaw.stat(obs, pop = 1, zloc, xmin = 1, zetatable = NULL)

Arguments

obs	Numeric vector of observation values.
pop	Numeric vector of population values; default = 1.
zloc	Numeric vector of selected nodes.
xmin	The minmum value of power law distribution; defaut=1.
zetatable	When xmin=1, set up the data(zetatable).

Value

Three values will be returned. The first value is test statistic. The second is the estimated means which estimated outside the selected nodes. The third is the estimated means estimated within the selected nodes.

Author(s)

Taichi Wang <[e-mail]>

References

Wang, T. C., Phoa, F. K. H., & Hsu, T. C. (2015). Power-law distributions of attributes in community detection. Social Network Analysis and Mining, 5(1), 1-10.

See Also

rplcon,zetatable,powerlaw.stat

Examples

library(poweRlaw)
x=rplcon(n=100, xmin=1, alpha=3)#function from poweRlaw
conpowerlaw.stat(obs=x,zloc=1:5)

taichi43/SNscan documentation built on May 31, 2019, 2:48 a.m.