eigenmodel: Semiparametric factor and regression models for symmetric relational data
Version 1.01

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.

Getting started

Package details

AuthorPeter Hoff
Date of publication2012-03-23 21:45:14
MaintainerPeter Hoff <[email protected]>
URL http://www.stat.washington.edu/hoff
Package repositoryView on CRAN
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eigenmodel documentation built on May 29, 2017, 8:12 p.m.