Estimation of the parameters in a model for symmetric relational data (e.g., the abovediagonal part of a square matrix), using a modelbased eigenvalue decomposition and regression. Missing data is accommodated, 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. See Hoff (2007) <arXiv:0711.1146> for details on the model.
Package details 


Author  Peter Hoff 
Maintainer  Peter Hoff <[email protected]> 
License  GPL2 
Version  1.10 
URL  https://pdhoff.github.io/ 
Package repository  View on GitHub 
Installation 
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