Returns the mean correlation at each drop proportion for each measure.
Usage
# S3 method for class 'net_stability'
summary(object, ...)Examples
# \donttest{
set.seed(1)
seqs <- data.frame(
V1 = sample(c("A","B","C"), 30, TRUE),
V2 = sample(c("A","B","C"), 30, TRUE),
V3 = sample(c("A","B","C"), 30, TRUE)
)
net <- build_network(seqs, method = "relative")
stab <- centrality_stability(net, measures = c("InStrength","OutStrength"),
iter = 10)
summary(stab)
#> measure drop_prop mean_cor sd_cor prop_above
#> 1 InStrength 0.1 0.9222246 0.08733393 1.0000000
#> 2 InStrength 0.2 0.5991203 0.40939988 0.5000000
#> 3 InStrength 0.3 0.8122252 0.19362303 0.7000000
#> 4 InStrength 0.4 0.4092091 0.78743599 0.6000000
#> 5 InStrength 0.5 0.1002185 0.76460340 0.3000000
#> 6 InStrength 0.6 0.7769158 0.14463237 0.7000000
#> 7 InStrength 0.7 -0.3303545 0.83617633 0.2000000
#> 8 InStrength 0.8 0.2274100 0.74756117 0.3000000
#> 9 InStrength 0.9 0.4906391 0.58239756 0.4444444
#> 10 OutStrength 0.1 0.9778194 0.01855856 1.0000000
#> 11 OutStrength 0.2 0.8194689 0.24134040 0.8000000
#> 12 OutStrength 0.3 0.8599518 0.15567073 0.8000000
#> 13 OutStrength 0.4 0.8882647 0.15233279 0.9000000
#> 14 OutStrength 0.5 0.6882411 0.59774050 0.8000000
#> 15 OutStrength 0.6 0.1968403 0.74154752 0.4000000
#> 16 OutStrength 0.7 0.4776833 0.62724172 0.5000000
#> 17 OutStrength 0.8 0.3197964 0.44307581 0.2000000
#> 18 OutStrength 0.9 0.4301138 0.41200379 0.2222222
# }