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Estimation and Simulation of Multi-Binary Response Models

v0.2.1.0 · Feb 12, 2026 · MIT + file LICENSE

Description

Multi-binary response models are a class of models that allow for the estimation of multiple binary outcomes simultaneously. This package provides functions to estimate and simulate these models using the Discrete Exponential-Family Models [DEFM] framework. In it, we implement the models described in Vega Yon, Valente, and Pugh (2023) <doi:10.48550/arXiv.2211.00627>. DEFMs include Exponential-Family Random Graph Models [ERGMs], which characterize graphs using sufficient statistics, which is also the core of DEFMs. Using sufficient statistics, we can describe the data through meaningful motifs, for example, transitions between different states, joint distribution of the outcomes, etc.

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  installed size is  6.4Mb
  sub-directories of 1Mb or more:
    libs   6.1Mb
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installed package size

  installed size is  6.7Mb
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NOTE 12 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026
NOTE r-oldrel-macos-arm64

installed package size

  installed size is  6.4Mb
  sub-directories of 1Mb or more:
    libs   6.1Mb
NOTE r-oldrel-macos-x86_64

installed package size

  installed size is  6.7Mb
  sub-directories of 1Mb or more:
    libs   6.3Mb

Dependency Network

Dependencies Reverse dependencies stats4 Rcpp defm

Version History

new 0.2.1.0 Mar 10, 2026