Description Usage Arguments Value Examples
This function aims at clustering the marginal network, inferred from edges probabilities obtained with either nestorFit()
or EMtree()
.
1 | init_blockmodels(sigma_O, MO, SO, k = 3, alpha = 0.1, cores = 1)
|
sigma_O |
PLNmodels output: covariance matrix estimate. |
MO |
PLNmodels output: observed means estimate. |
SO |
PLNmodels output: observed marginal variances estimate. |
k |
Number of groups to find. |
alpha |
Tempering parameter. |
cores |
Number of cores for parallel computation (uses mclapply, not available for Windows). |
A list of cliques
1 2 3 4 5 6 7 8 | data=generate_missing_data(n=100,p=10,r=1,type="scale-free", plot=TRUE)
data$TC
PLNfit<-norm_PLN(data$Y)
MO<-PLNfit$MO
SO<-PLNfit$SO
sigma_O=PLNfit$sigma_O
#-- initialize with blockmodels
init_blockmodels(sigma_O, MO, SO, k=2 )
|
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