View source: R/backbone.extract.R
backbone.extract | R Documentation |
backbone.extract
returns a binary or signed adjacency matrix
containing the backbone that retains only the significant edges.
backbone.extract(
bb.object,
signed = FALSE,
alpha = 0.05,
mtc = "none",
class = bb.object$class,
narrative = FALSE
)
bb.object |
backbone: backbone S3 class object. |
signed |
boolean: TRUE for a signed backbone, FALSE for a binary backbone (see details) |
alpha |
real: significance level of hypothesis test(s) |
mtc |
string: type of Multiple Test Correction to be applied; can be any method allowed by |
class |
string: the class of the returned backbone graph, one of c("matrix", "sparseMatrix", "igraph", "edgelist"), converted via tomatrix. |
narrative |
boolean: TRUE if suggested text & citations should be displayed. |
The "backbone" S3 class object is composed of (1) the weighted graph as a matrix, (2) upper-tail p-values as a
matrix, (3, if signed = TRUE
) lower-tail p-values as a matrix, (4, if present) node attributes as a dataframe, and
(5) several properties of the original graph and backbone model
When signed = FALSE
, a one-tailed test (is the weight stronger?) is performed for each edge. The resulting backbone
contains edges whose weights are significantly stronger than expected in the null model. When signed = TRUE
, a
two-tailed test (is the weight stronger or weaker?) is performed for each edge. The resulting backbone contains
positive edges for those whose weights are significantly stronger, and negative edges for those whose weights are
significantly weaker, than expected in the null model.
backbone graph: Binary or signed backbone graph of class given in parameter class
.
#A binary bipartite network of 30 agents & 75 artifacts; agents form three communities
B <- rbind(cbind(matrix(rbinom(250,1,.8),10),
matrix(rbinom(250,1,.2),10),
matrix(rbinom(250,1,.2),10)),
cbind(matrix(rbinom(250,1,.2),10),
matrix(rbinom(250,1,.8),10),
matrix(rbinom(250,1,.2),10)),
cbind(matrix(rbinom(250,1,.2),10),
matrix(rbinom(250,1,.2),10),
matrix(rbinom(250,1,.8),10)))
backbone.object <- fixedrow(B, alpha = NULL)
bb <- backbone.extract(backbone.object, alpha = 0.05)
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