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eigenmodel  

Semiparametric Factor and Regression Models for Symmetric Relational Data
View on CRAN: Click here


Download and install eigenmodel package within the R console
Install from CRAN:
install.packages("eigenmodel")

Install from Github:
library("remotes")
install_github("cran/eigenmodel")

Install by package version:
library("remotes")
install_version("eigenmodel", "1.12")



Attach the package and use:
library("eigenmodel")
Maintained by
Peter Hoff
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2007-06-27
Latest Update: 2019-05-28
Description:
Estimation of the parameters in 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 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) for details on the model.
How to cite:
Peter Hoff (2007). eigenmodel: Semiparametric Factor and Regression Models for Symmetric Relational Data. R package version 1.12, https://cran.r-project.org/web/packages/eigenmodel. Accessed 05 Jun. 2026.
Previous versions and publish date:
1.0 (2007-06-27 11:32), 1.01 (2012-03-23 22:45), 1.10 (2018-06-03 16:57), 1.11 (2019-05-28 17:40)
Other packages that cited eigenmodel R package
View eigenmodel citation profile
Other R packages that eigenmodel depends, imports, suggests or enhances
Complete documentation for eigenmodel
Functions, R codes and Examples using the eigenmodel R package
Some associated functions: ULU . XB . YX_Friend . Y_Gen . Y_Pro . Y_impute . addlines . eigenmodel-package . eigenmodel_mcmc . eigenmodel_setup . plot.eigenmodel_post . rUL_fc . rZ_fc . rb_fc . rmvnorm . 
Some associated R codes: ULU.R . XB.R . Y_impute.R . addlines.R . eigenmodel-package.R . eigenmodel_mcmc.R . eigenmodel_setup.R . plot.eigenmodel_post.R . rUL_fc.R . rZ_fc.R . rb_fc.R . rmvnorm.R .  Full eigenmodel package functions and examples
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