sample_dclvm.Rd
A DCLVM with K clusters has edges generated as
E[Aij∣x,θ]∝θiθje−‖xi−xj‖2andxi=2ezi+wi
where ek is the kth basis vector of Rd, wi∼N(0,Id),
and {zi}⊂[K]n. The proportionality constant is chosen such
that the overall network has expected average degree λ.
To calculate the scaling constant, we approximate E[e−‖xi−xj‖2]
for i≠j by generating random npairs
{zi,zj} and average over them.
sample_dclvm(z, lambda, theta, npairs = NULL)
a vector of cluster labels
desired average degree of the network
degree parameter
number of pairs of {zi,zj}
Sample form a degree-corrected latent variable model with Gaussian kernel