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This performs an iterative relaxation type algorithm to approximately find the positions of the nodes in the latent space that maximises the log-likelihood.
log_like_forces(net, D, X, B, m ,steps)
Matrix of latent positions X
network object on which to perform layout.
dimension of the latent space.
the initial guess for X
the intercept term.
usually N will suffice.
maximum number of iteration steps.
Michael Salter-Townshend
Usually only used internally in vblpcmstart()
igraph::layout.fruchterman.reingold
data(sampson) N=network.size(samplike) X=matrix(runif(N*2,-2,2),ncol=2) XX=vblpcmcovs(N,"plain",as.sociomatrix(samplike)) out<-log_like_forces(samplike, 2, X, 0, m=N, 1e3) plot(samplike,coord=out$X)
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