Description Usage Arguments Value Author(s) References See Also Examples
collpcm.fit
is used to fit the latent position cluster model with uncertainty in the number of clusters incorporated. A posterior distribution for the number of clusters is estimated.
1 | collpcm.fit( Y , d = 2, G = NULL, Gmax = NULL, control = list(), Xref = NA )
|
Y |
A network object containing the network in question. |
d |
The dimension of the latent position to represent each node in the network (defaults to 2). |
G |
Give the initial number of groups for the algorithm. |
Gmax |
Give the maximum allowed number of groups if doing model search. |
control |
List giving the set up of the algorithm (see |
Xref |
Optional latent positions to be used as a reference configuration for the Procrustes rotations. |
collpcm.fit
returns an object of class collpcm
that is a list.
The list will have the following slots.
call |
The values of each of the arguments used in the model fitting MCMC run. |
sample |
A list containing the samples from the MCMC run. |
Gpost |
Estimated posterior distribution of the number of groups/clusters. |
Xpostmean |
Estimated posterior mean from sampled latent positions. |
XpostMKL |
MKL posterior latent positions as described in Handcock, Raftery & Tantrum (2007). |
Gslot |
An indexing vector for the lists of posterior mean and MKL positions. |
acceptance.rates |
Acceptance rates for different moves of MCMC algorithm. |
adapted.sd.prop |
The standard deviations of the proposal distributions after the adaptation phase. |
timings |
A list of timings for each part of the algorithm. |
Jason Wyse
Ryan, C., Wyse, J. and Friel, N. (2017). Bayesian model selection for the latent position cluster model for Social Networks. Network Science, volume 5, 70-91.
Handcock, M. S., Raftery, A. E. and Tantrum, J. (2007). Model-Based Clustering for Social Networks. Journal of the Royal Statistical Society, Series A, Vol. 170, 301-354 <doi: 10.1111/j.1467-985X.2007.00471.x>
collpcm.control
1 2 3 4 5 6 7 8 9 10 |
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.