# inst/doc/threshold_graph.R In netrankr: Analyzing Partial Rankings in Networks

```## ----setup-blind,include=FALSE------------------------------------------------
library(Matrix)

## ----setup, warning=FALSE,message=FALSE---------------------------------------
library(netrankr)
library(igraph)
set.seed(1886) #for reproducibility

## ----tg_creation--------------------------------------------------------------
g1 <- threshold_graph(500,0.4)
g2 <- threshold_graph(500,0.05)

c(round(graph.density(g1),2), round(graph.density(g2),2))

## ----tg_example,fig.show='hold'-----------------------------------------------
star <- threshold_graph(6,0)
complete <- threshold_graph(6,1)
plot(star,vertex.label=NA,vertex.color="black")
plot(complete,vertex.label=NA,vertex.color="black")

## ----tg_complete--------------------------------------------------------------
g <- threshold_graph(10,0.4)
P <- neighborhood_inclusion(g)
comparable_pairs(P)

## ----tg_cent------------------------------------------------------------------
g <- threshold_graph(100,0.1)

cent.df <- data.frame(
degree=degree(g),
betweenness=betweenness(g),
closeness=closeness(g),
eigenvector=round(eigen_centrality(g)\$vector,8),
subgraph=subgraph_centrality(g)
)

## ----cor_tg-------------------------------------------------------------------
cor.mat <- cor(round(cent.df,8),method="kendall")
cor.mat <- round(cor.mat,2)
cor.mat

## ----compare_ranks------------------------------------------------------------
comp <- compare_ranks(cent.df\$degree,cent.df\$betweenness)
unlist(comp)

## ----discordant---------------------------------------------------------------
dis.pairs <- matrix(0,5,5)
dis.pairs[1,] <- apply(cent.df,2,
function(x)compare_ranks(cent.df\$degree,x)\$discordant)
dis.pairs[2,] <- apply(cent.df,2,
function(x)compare_ranks(cent.df\$betweenness,x)\$discordant)
dis.pairs[3,] <- apply(cent.df,2,
function(x)compare_ranks(cent.df\$closeness,x)\$discordant)
dis.pairs[4,] <- apply(cent.df,2,
function(x)compare_ranks(cent.df\$eigenvector,x)\$discordant)
dis.pairs[5,] <- apply(cent.df,2,
function(x)compare_ranks(cent.df\$subgraph,x)\$discordant)
dis.pairs

## ----major_gap----------------------------------------------------------------
tg <- threshold_graph(200,0.2)
majorization_gap(g)

## ----major_gap_ex_norm--------------------------------------------------------
data("dbces11")
g <- dbces11

majorization_gap(g)

## ----major_gap_ex_not_norm----------------------------------------------------
majorization_gap(g,norm = FALSE)
```

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netrankr documentation built on Sept. 27, 2022, 1:07 a.m.