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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  7 months and 10 days ago 561 main
conda 911.0 kB | noarch/r-mlergm-0.8-r44hc72bb7e_3.conda  7 months and 10 days ago 593 main
conda 910.1 kB | noarch/r-mlergm-0.8-r42hc72bb7e_2.conda  1 year and 8 months ago 1020 main
conda 909.5 kB | noarch/r-mlergm-0.8-r43hc72bb7e_2.conda  1 year and 8 months ago 1031 main
conda 941.2 kB | noarch/r-mlergm-0.8-r41hc72bb7e_1.tar.bz2  2 years and 5 months ago 1444 main
conda 943.5 kB | noarch/r-mlergm-0.8-r42hc72bb7e_1.tar.bz2  2 years and 5 months ago 1452 main
conda 948.1 kB | noarch/r-mlergm-0.8-r40hc72bb7e_0.tar.bz2  3 years and 5 months ago 2093 main
conda 950.3 kB | noarch/r-mlergm-0.8-r41hc72bb7e_0.tar.bz2  3 years and 5 months ago 2155 main

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