estimateMultiplexSBM: Estimation for Multiplex SBM

Description Usage Arguments Details Value Examples

View source: R/estimate.R

Description

Estimation for Multiplex SBM

Usage

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estimateMultiplexSBM(listSBM, dependent = FALSE, estimOptions = list())

Arguments

listSBM

list of networks that were defined by the defineSBM function

dependent

logical parameter indicating whether the networks in the multiplex structure are dependent beyond the latent variables,

estimOptions

options for the inference procedure

Details

The list of parameters estimOptions essentially tunes the optimization process and the variational EM algorithm. See the details in the function "estimateMultipartiteSBM" if dependent=FALSE, details in the function "estimateSimpleSBM" otherwise.

Value

a MultiplexSBM_fit object with the estimated parameters and the blocks

Examples

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## MultiplexSBM without dependence between layers
Nnodes <- 40
blockProp <- c(.4,.6)
nbLayers <- 2
connectParam <- list(list(mean=matrix(rbeta(4,.5,.5),2,2)),list(mean=matrix(rexp(4,.5),2,2)))
model <- c("bernoulli","poisson")
type <- "directed"
mySampleMultiplexSBM <-
   sampleMultiplexSBM(
   nbNodes = Nnodes,
    blockProp = blockProp,
   nbLayers = nbLayers,
   connectParam = connectParam,
   model=model,
   type=type)
listSBM <- mySampleMultiplexSBM$listSBM
estimOptions <- list(initBM = FALSE, nbCores  = 2)
myMultiplexSBM <- estimateMultiplexSBM(listSBM,estimOptions,dependent=FALSE)
## MultiplexSBM Gaussian with dependence
Q <- 3
nbLayers <- 2
connectParam <- list()
connectParam$mu <- vector("list",nbLayers)
connectParam$mu[[1]] <-  matrix(.1,Q,Q) + diag(1:Q)
connectParam$mu[[2]] <- matrix(-2,Q,Q) + diag(rev(Q:1))
connectParam$Sigma <- matrix(c(2,1,1,4),nbLayers,nbLayers)
model <- rep("gaussian",2)
type <- "directed"
Nnodes <- 80
blockProp <- c(.3,.3,.4)
mySampleMultiplexSBM <-
  sampleMultiplexSBM(
     nbNodes = Nnodes,
     blockProp = blockProp,
     nbLayers = nbLayers,
     connectParam = connectParam,
     model=model,
     type="undirected",
     dependent=TRUE)
listSBM <- mySampleMultiplexSBM$listSBM
myMultiplexSBM <- estimateMultiplexSBM(listSBM,estimOptions,dependent=TRUE)
## MultiplexSBM Bernoulli with dependence
Q <- 2
P00<-matrix(runif(Q*Q),Q,Q)
P10<-matrix(runif(Q*Q),Q,Q)
P01<-matrix(runif(Q*Q),Q,Q)
P11<-matrix(runif(Q*Q),Q,Q)
SumP<-P00+P10+P01+P11
P00<-P00/SumP
P01<-P01/SumP
P10<-P10/SumP
P11<-P11/SumP
connectParam <- list()
connectParam$prob00 <- P00
connectParam$prob01 <- P01
connectParam$prob10 <- P10
connectParam$prob11 <- P11
model <- rep("bernoulli",2)
type <- "directed"
nbLayers <- 2
Nnodes <- 40
blockProp <- c(.6,.4)
mySampleMultiplexSBM <-
   sampleMultiplexSBM(
     nbNodes = Nnodes,
     blockProp = blockProp,
     nbLayers = nbLayers,
     connectParam = connectParam,
     model=model,
     type=type,
     dependent=TRUE)
listSBM <- mySampleMultiplexSBM$listSBM
myMultiplexSBM <- estimateMultiplexSBM(listSBM,estimOptions,dependent=TRUE)

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