mpmm.generate: Generate data from the MPMM.

In mpmm: Marginal Product Mixture Model for Relational Event Data

Description

[describe generative model]

Usage

mpmm.generate(T, params, dims)

Arguments

T	Number of events to simulate.
params	A list with the following variables: C number of latent classes pi vector of length C, denoting the probability of each latent class phi a list with 3 elements (one for each dimension). Each element is a C x N_d matrix denoting the probability of choosing a particular actor i given the event has latent class c (where N_d is the number of possible actors in dimension d).
dims	a vector containing the number of possible actors for each dimension

Value

dataset	a matrix with T rows and 3 columns, where the d'th column contains integers in [1,...,N_d]
assignments	a vector of the class assigned to each event

Author(s)

Christopher DuBois (<email: [e-mail]>)

References

Christopher DuBois and Padhraic Smyth. Modeling Relational Events via Latent Classes. Proceedings of the 16th ACM SIGKDD, 2010.

See Also

mpmm.cgs

Examples

## See demo(synthetic) and demo(enron).

mpmm documentation built on May 2, 2019, 4:55 p.m.