This package implements the Marginal Product Mixture Model (MPMM) for relational event data. Inference for the model is implemented via a collapsed Gibbs sampler written in C. Utility functions for processing sets of relational events, displaying posterior predictive distributions, and fitting baseline models are also included.
|Date of publication||None|
|Maintainer||Christopher DuBois <firstname.lastname@example.org>|
enron: Enron email data.
mpmm.cgs: Collapsed Gibbs sampler for the marginal product mixture...
mpmm.generate: Generate data from the MPMM.
mpmm-internal: Internal mpmm objects
mpmm-package: Marginal Product Mixture Model for Relational Event Data
mpmm.plotassignments: Plot the latent class assigned to each observed event.
mpmm.plotphi: Plot model parameters.
mpmm.predict: Predict probability of events given model parameters.
mult.dir: Fit a multinomial with a Dirichlet prior to the observed...
plotmat: Plot a matrix.
reddeer: Red Deer dataset.