R6 class for Simple SBM

R6 class for Simple SBM

`sbm::SBM`

-> `SimpleSBM`

`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

`new()`

constructor for SBM

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

`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

`rMemberships()`

a method to sample new block memberships for the current SBM

SimpleSBM$rMemberships(store = FALSE)

`store`

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

the sampled blocks

`rEdges()`

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

SimpleSBM$rEdges(store = FALSE)

`store`

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

the sampled network

`predict()`

prediction under the currently parameters

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

`covarList`

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

`theta_p0`

a threshold...

a matrix of expected values for each dyad

`show()`

show method

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

`type`

character used to specify the type of SBM

`plot()`

basic matrix plot method for SimpleSBM object or mesoscopic plot

`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.

a ggplot2 object for the `'data'`

and `'expected'`

, a list with the igraph object `g`

, the `layout`

and the `plotOptions`

for the `'meso'`

`clone()`

The objects of this class are cloneable with this method.

SimpleSBM$clone(deep = FALSE)

`deep`

Whether to make a deep clone.