loglikelihood_prime_bicm

vector, probabilities given by current step in bicm function

list, c(degree sequence of rows, degree sequence of cols, multiplicity of rows, multiplicity of columns)

args

Computes the loglikelihood gradient for the <a rd-options="" href="/link/bicm?package=backbone&version=1.4.0" data-mini-rdoc="backbone::bicm">bicm</a> function

internal

Provides methods for extracting from a weighted graph
a binary or signed backbone that retains only the significant edges.
The user may input a weighted graph, or a bipartite graph
from which a weighted graph is first constructed via projection.
Backbone extraction methods include the stochastic degree sequence model (Neal, Z. P. (2014). <doi:10.1016/j.socnet.2014.06.001>),
hypergeometric model (Neal, Z. (2013). <doi:10.1007/s13278-013-0107-y>),
the fixed degree sequence model (Zweig, K. A., and Kaufmann, M. (2011). <doi:10.1007/s13278-011-0021-0>),
fixed column model, fixed fill model,
as well as a universal threshold method.

Rachel Domagalski

backbone

Extracts the Backbone from Weighted Graphs

Zachary Neal

Bruce Sagan

loglikelihood_prime_bicm function

Computes the loglikelihood gradient for the <a rd-options='' href='bicm'>bicm</a> function

Computes the loglikelihood gradient for the <a rd-options='' href='bicm'>bicm</a> function — loglikelihood_prime_bicm

Computes the loglikelihood gradient for the <a rd-options='' href='bicm'>bicm</a> function

Computes the loglikelihood gradient for the <a rd-options="" href="/link/bicm?package=backbone&version=1.4.0" data-mini-rdoc="backbone::bicm">bicm</a> function

loglikelihood_prime_bicm: Computes the loglikelihood gradient for the bicm function

Description

Usage

Arguments

Value