eigenmodel

Semiparametric Factor and Regression Models for Symmetric Relational Data

CRAN Package

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) doi:10.48550/arXiv.0711.1146 for details on the model.

  • Version1.11
  • R versionunknown
  • LicenseGPL-2
  • Needs compilation?No
  • Last release05/28/2019

Documentation


Team


Insights

Last 30 days

Last 365 days

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Data provided by CRAN


Binaries


Dependencies

  • Reverse Imports1 package
  • Reverse Suggests1 package