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Estimates exponential-family random graph models for multilevel network data, assuming the multilevel structure is observed. The scope, at present, covers multilevel models where the set of nodes is nested within known blocks. The estimation method uses Monte-Carlo maximum likelihood estimation (MCMLE) methods to estimate a variety of canonical or curved exponential family models for binary random graphs. MCMLE methods for curved exponential-family random graph models can be found in Hunter and Handcock (2006) <DOI: 10.1198/106186006X133069>. The package supports parallel computing, and provides methods for assessing goodness-of-fit of models and visualization of networks.

copied from cf-staging / r-mlergm
Type Size Name Uploaded Downloads Labels
conda 909.9 kB | noarch/r-mlergm-0.8-r43hc72bb7e_3.conda  6 months and 27 days ago 538 main
conda 911.0 kB | noarch/r-mlergm-0.8-r44hc72bb7e_3.conda  6 months and 27 days ago 569 main
conda 910.1 kB | noarch/r-mlergm-0.8-r42hc72bb7e_2.conda  1 year and 8 months ago 1002 main
conda 909.5 kB | noarch/r-mlergm-0.8-r43hc72bb7e_2.conda  1 year and 8 months ago 1010 main
conda 941.2 kB | noarch/r-mlergm-0.8-r41hc72bb7e_1.tar.bz2  2 years and 4 months ago 1421 main
conda 943.5 kB | noarch/r-mlergm-0.8-r42hc72bb7e_1.tar.bz2  2 years and 4 months ago 1429 main
conda 948.1 kB | noarch/r-mlergm-0.8-r40hc72bb7e_0.tar.bz2  3 years and 4 months ago 2072 main
conda 950.3 kB | noarch/r-mlergm-0.8-r41hc72bb7e_0.tar.bz2  3 years and 4 months ago 2134 main

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