| latentnet {latentnet} | R Documentation |
The package latentnet is used to fit latent cluster
models, where the probability of a network g,
on a set of nodes is a product of dyad probabilities, each of which is
a GLM with linear component
eta_{i,j}=sum_{k=1}^p β_k X_{i,j,k}+||Z_i-Z_j||,
where X is an array of dyad covariates, β is a vector
of covariate coefficients and Z_i is the latent space position of
node i.
The ergmm specifies models via: g ~ <model terms>
where g is a network object
For the list of possible <model terms>, see
terms.ergmm.
The arguments in the ergmm function specific to latent
variable models
are ergmm.control. See the help page for ergmm for the
details.
The result of a latent variable model fit is an ergmm object.
Hence the summary, print, and plot functions
apply to the fits.
The plot.ergmm function has many options specific to latent
variable models.
See the help page for plot.ergmm for the details.
ergmm returns an object of class 'ergmm' that is a list.
Peter D. Hoff, Adrian E. Raftery and Mark S. Handcock. Latent space approaches to social network analysis. Journal of the American Statistical Association, Dec 2002, Vol. 97, Iss. 460; pg. 1090-1098.
Mark S. Handcock, Adrian E. Raftery and Jeremy Tantrum. Model-Based Clustering for Social Networks. Journal of the Royal Statistical Society: Series A (Statistics in Society), 2007, Vol. 170, Iss. 2; pg. 301-354.
Susan M. Shortreed, Mark S. Handcock, and Peter D. Hoff. Positional Estimation within the Latent Space Model for Networks. Methodology, 2006, Vol. 2, Iss. 1; pg. 24-33.