Summary Method for net_permutation
Usage
# S3 method for class 'net_permutation'
summary(object, ...)Examples
s1 <- data.frame(V1 = c("A","B","C"), V2 = c("B","C","A"))
s2 <- data.frame(V1 = c("A","C","B"), V2 = c("C","B","A"))
n1 <- build_network(s1, method = "relative")
n2 <- build_network(s2, method = "relative")
perm <- permutation(n1, n2, iter = 10)
summary(perm)
#> from to weight_x weight_y diff effect_size p_value sig
#> 1 A B 1 0 1 1.333333 0.5454545 FALSE
#> 2 A C 0 1 -1 -1.267449 0.5454545 FALSE
#> 3 B A 0 1 -1 -1.360828 0.4545455 FALSE
#> 4 B C 1 0 1 1.360828 0.4545455 FALSE
#> 5 C A 1 0 1 1.237969 0.7272727 FALSE
#> 6 C B 0 1 -1 -1.184698 0.7272727 FALSE
# \donttest{
set.seed(1)
d1 <- data.frame(V1 = c("A","B","A"), V2 = c("B","C","B"),
V3 = c("C","A","C"))
d2 <- data.frame(V1 = c("C","A","C"), V2 = c("A","B","A"),
V3 = c("B","C","B"))
net1 <- build_network(d1, method = "relative")
net2 <- build_network(d2, method = "relative")
perm <- permutation(net1, net2, iter = 20, seed = 1)
summary(perm)
#> from to weight_x weight_y diff effect_size p_value sig
#> 1 A B 1 1 0 0 1 FALSE
#> 2 B C 1 1 0 0 1 FALSE
#> 3 C A 1 1 0 0 1 FALSE
# }