edgeList | R Documentation |
Convert a coincidence/similarity/distance matrix into an edge list form.
edgeList(data, procedures="Haberman",
criteria="Z", level=.95, Bonferroni=FALSE,
min=-Inf, max=Inf, support=-Inf, directed=FALSE,
diagonal=FALSE, sort=NULL, decreasing=TRUE, pairwise=FALSE)
data |
a coin object, let's say an R matrix with frequencies and an attribute ( |
procedures |
a vector of statistics of similarity. See below. |
criteria |
statistic to be use for selection criteria. |
level |
confidence level |
Bonferroni |
Bonferroni criterium of the signification test. |
min |
minimum value of the statistic to include the edge in the list. |
max |
maximum value of the statistic to include the edge in the list. |
support |
minimum value of the frequency of the coincidence to be edged |
directed |
includes same edges only once. |
diagonal |
includes auto-links |
sort |
sort the list according to the values of a statistic. See below |
decreasing |
order in a decreasing way. |
pairwise |
Pairwise mode of handling missing values if TRUE. Listwise by default. |
Possible measures in procedures are
Frequencies (f), Relative frequencies (x), Conditional frequencies (i), Coincidence degree (cc), Probable degree (cp),
Expected (e), Confidence interval (con)
Matching (m), Rogers & Tanimoto (t), Gower (g), Sneath (s), Anderberg (and),
Jaccard (j), Dice (d), antiDice (a), Ochiai (o), Kulczynski (k),
Hamann (ham), Yule (y), Pearson (p), odds ratio (od), Rusell (r),
Haberman (h), Z value of Haberman (z),
Hypergeometric p greater value (hyp).
Convert a matrix into an edge list (shape).
A data frame in which the two first columns are source and target. The rest of the columns are the different statistics explicited in funcs
parameter.
Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/
Escobar, M. and Martinez-Uribe, L. (2020)
Network Coincidence Analysis: The netCoin
R
Package.
Journal of Statistical Software, 93, 1-32.
\Sexpr[results=rd]{tools:::Rd_expr_doi("10.18637/jss.v093.i11")}.
# From a random incidence matrix I(25X4)
I<-matrix(rbinom(100,1,.5),nrow=25,ncol=4,
dimnames=list(NULL,c("A","B","C","D")))
C<-coin(I)
edgeList(C)
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