beam.select-class: Class beam.select

In beam: Fast Bayesian Inference in Large Gaussian Graphical Models

Description

An S4 class representing the output of the beam.select function.

Usage

  ## S4 method for signature 'beam.select'
print(x, ...)

  ## S4 method for signature 'beam.select'
show(object)

  ## S4 method for signature 'beam.select'
summary(object, ...)
  
  ## S4 method for signature 'beam.select'
marg(object)

  ## S4 method for signature 'beam.select'
cond(object)

  ## S4 method for signature 'beam.select'
mcor(object)
  
  ## S4 method for signature 'beam.select'
pcor(object)

  ## S4 method for signature 'beam.select'
plotML(object, ...)

  ## S4 method for signature 'beam.select'
plotAdj(object, type=object@type, order = "original")

  ## S4 method for signature 'beam.select'
bgraph(object)

  ## S4 method for signature 'beam.select'
ugraph(object)

Arguments

x	An object of class beam.select-class
object	An object of class beam.select-class
type	character. Type of correlation to be displayed (marginal, conditional or both)
order	character. Either 'original' or 'clust'. If 'clust' the rows and columns of the adjacency matrix are reordered using the cluster memberships obtained by the Louvain clustering algorithm.
...	further arguments passed to or from other methods.

Slots

marginal

data.frame. A data.frame containing the marginal correlation estimates, Bayes factors and tail probabilities for the selected edges only.

conditional

data.frame. A data.frame containing the partial correlation estimates, Bayes factors and tail probabilities for the selected edges only.

dimX

numeric. Dimension of the imput data matrix X.

type

character. Input type (marginal, conditional or both)

varlabs

character. Column labels of X.

alphaOpt

numeric. Empirical Bayes estimates of hyperpaprameter alpha.

gridAlpha

matrix. A matrix containing the log-marginal likelihood of the Gaussian conjugate model as a function of a grid of values of alpha and delta.

valOpt

numeric. Maximum value of the log-marginal likelihood of the Gaussian conjugate model

method

character. Input method.

thres

numeric. Input threshold

Author(s)

Gwenael G.R. Leday and Ilaria Speranza

beam documentation built on July 1, 2020, 10:23 p.m.