SBM.estimate: estimates SBM parameters given community labels
In randnet: Random Network Model Estimation, Selection and Parameter Tuning
SBM.estimate R Documentation
estimates SBM parameters given community labels
Description
estimates SBM parameters given community labels
Usage
SBM.estimate(A, g)
Arguments
A
adjacency matrix
g
a vector of community labels
Details
maximum likelhood is used
Value
a list of
B
estimated block connection probability matrix
Phat
estimated probability matrix
g
community labels
Author(s)
Tianxi Li, Elizaveta Levina, Ji Zhu
Maintainer: Tianxi Li tianxili@virginia.edu
References
B. Karrer and M. E. Newman. Stochastic blockmodels and community structure in networks.
Physical Review E, 83(1):016107, 2011.
See Also
DCSBM.estimate
Examples
dt <- BlockModel.Gen(30,300,K=3,beta=0.2,rho=0)
A <- dt$A
sc <- reg.SP(A,K=3,lap=TRUE)
sbm <- SBM.estimate(A,sc$cluster)
sbm$B
randnet documentation built on May 31, 2023, 6:44 p.m.
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| SBM.estimate | R Documentation |
estimates SBM parameters given community labels
Description
estimates SBM parameters given community labels
Usage
SBM.estimate(A, g)
Arguments
A |
adjacency matrix |
g |
a vector of community labels |
Details
maximum likelhood is used
Value
a list of
B |
estimated block connection probability matrix |
Phat |
estimated probability matrix |
g |
community labels |
Author(s)
Tianxi Li, Elizaveta Levina, Ji Zhu
Maintainer: Tianxi Li tianxili@virginia.edu
References
B. Karrer and M. E. Newman. Stochastic blockmodels and community structure in networks. Physical Review E, 83(1):016107, 2011.
See Also
DCSBM.estimate
Examples
dt <- BlockModel.Gen(30,300,K=3,beta=0.2,rho=0)
A <- dt$A
sc <- reg.SP(A,K=3,lap=TRUE)
sbm <- SBM.estimate(A,sc$cluster)
sbm$B
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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