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 with a non-zero weight. It
yields a backbone that perserves edges whose weights are significantly *stronger* than expected in the chosen null
model. When `signed = TRUE`

, a two-tailed test (is the weight stronger or weaker) is performed for each every pair of nodes.
It yields a backbone that contains positive edges for edges whose weights are significantly *stronger*, and
negative edges for edges whose weights are significantly *weaker*, than expected in the chosen null model.
*NOTE: Before v2.0.0, all significance tests were two-tailed and zero-weight edges were evaluated.*

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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