SimpleSBM: R6 class for Simple SBM

Description Super class Active bindings Methods

Description

R6 class for Simple SBM

R6 class for Simple SBM

Super class

sbm::SBM -> SimpleSBM

Active bindings

dimLabels

a single character giving the label of the nodes

blockProp

vector of block proportions (aka prior probabilities of each block)

connectParam

parameters associated to the connectivity of the SBM, e.g. matrix of inter/inter block probabilities when model is Bernoulli

probMemberships

matrix of estimated probabilities for block memberships for all nodes

nbBlocks

number of blocks

nbDyads

number of dyads (potential edges in the network)

nbConnectParam

number of parameter used for the connectivity

memberships

vector of clustering

indMemberships

matrix for clustering memberships

Methods

Public methods

Inherited methods

Method new()

constructor for SBM

Usage
SimpleSBM$new(
  model,
  nbNodes,
  directed,
  blockProp,
  connectParam,
  dimLabels = c(node = "nodeName"),
  covarParam = numeric(length(covarList)),
  covarList = list()
)
Arguments
model

character describing the type of model

nbNodes

number of nodes in the network

directed

logical, directed network or not.

blockProp

parameters for block proportions (vector of list of vectors)

connectParam

list of parameters for connectivity with a matrix of means 'mean' and an optional scalar for the variance 'var'. The size of mu must match blockProp length

dimLabels

optional label for the node (default is "nodeName")

covarParam

optional vector of covariates effect

covarList

optional list of covariates data


Method rMemberships()

a method to sample new block memberships for the current SBM

Usage
SimpleSBM$rMemberships(store = FALSE)
Arguments
store

should the sampled blocks be stored (and overwrite the existing data)? Default to FALSE

Returns

the sampled blocks


Method rEdges()

a method to sample a network data (edges) for the current SBM

Usage
SimpleSBM$rEdges(store = FALSE)
Arguments
store

should the sampled edges be stored (and overwrite the existing data)? Default to FALSE

Returns

the sampled network


Method predict()

prediction under the currently parameters

Usage
SimpleSBM$predict(covarList = self$covarList, theta_p0 = 0)
Arguments
covarList

a list of covariates. By default, we use the covariates with which the model was estimated

theta_p0

a threshold...

Returns

a matrix of expected values for each dyad


Method show()

show method

Usage
SimpleSBM$show(type = "Simple Stochastic Block Model")
Arguments
type

character used to specify the type of SBM


Method plot()

basic matrix plot method for SimpleSBM object or mesoscopic plot

Usage
SimpleSBM$plot(
  type = c("data", "expected", "meso"),
  ordered = TRUE,
  plotOptions = list()
)
Arguments
type

character for the type of plot: either 'data' (true connection), 'expected' (fitted connection) or 'meso' (mesoscopic view). Default to 'data'.

ordered

logical: should the rows and columns be reordered according to the clustering? Default to TRUE.

plotOptions

list with the parameters for the plot. See help of the corresponding S3 method for details.

Returns

a ggplot2 object for the 'data' and 'expected', a list with the igraph object g, the layout and the plotOptions for the 'meso'


Method clone()

The objects of this class are cloneable with this method.

Usage
SimpleSBM$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.


GrossSBM/sbm documentation built on April 8, 2021, 5:53 a.m.