eigenmodel: Semiparametric factor and regression models for symmetric relational data

This package estimates the parameters of a model for symmetric relational data (e.g., the above-diagonal part of a square matrix), using a model-based eigenvalue decomposition and regression. Missing data is accomodated, and a posterior mean for missing data is calculated under the assumption that the data are missing at random. The marginal distribution of the relational data can be arbitrary, and is fit with an ordered probit specification.

Version: 1.01
Published: 2012-03-23
Author: Peter Hoff
Maintainer: Peter Hoff <hoff at stat.washington.edu>
License: GPL-2
URL: http://www.stat.washington.edu/hoff
NeedsCompilation: no
In views: Bayesian
CRAN checks: eigenmodel results


Reference manual: eigenmodel.pdf
Package source: eigenmodel_1.01.tar.gz
Windows binaries: r-devel: eigenmodel_1.01.zip, r-release: eigenmodel_1.01.zip, r-oldrel: eigenmodel_1.01.zip
OS X binaries: r-release: eigenmodel_1.01.tgz, r-oldrel: eigenmodel_1.01.tgz
Old sources: eigenmodel archive

Reverse dependencies:

Reverse suggests: sand


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