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Hello all,

I have made available on my web page some software for fitting
(generalized bilinear) mixed effects regression models for
dyadic network data. The software is written for the R statistical
programming environment. Some of the options for the model fitting
procedure are given at the bottom of this email. The software, some
examples using Poisson and logistic regression, and a preprint
detailing the model estimation procedures are available at:

http://www.stat.washington.edu/hoff/Code/GBME/

Regards,
Peter Hoff

-------------------------
Peter Hoff
Assistant Professor
Department of Statistics
206-221-6982
Box 354322
University of Washington
Seattle, WA  98195
_________________________


Usage: gbme(Y,Xd,Xs,Xr,...)

Data arguments:

    * Y is a square (nxn) sociomatrix. Missing (at random) data is allowed.
    * Xd is an nxnxrd array giving dyad-specific covariates.
    * Xs is an nxrs matrix of sender-specific covariates.
    * Xs is an nxrr matrix of receiver-specific covariates.

Model specification arguments (defaults in parentheses):

    * family ("gaussian") : can be "gaussian", "poisson" or "binomial"
    * directed (T) : logical denoting if the relation is directed or not.
    * k (0) : an integer denoting the dimension of the inner-product
              interaction

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