eigenmodel (1.01)

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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.

Maintainer: Peter Hoff
Author(s): Peter Hoff

License: GPL-2

Uses: Does not use any package

Released over 3 years ago.

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