rmixedMem: Simulate Data from a discrete mixed membership model
In ysamwang/mixedMem: Tools for Discrete Multivariate Mixed Membership Models

Description Usage Arguments Details Value

Simulate Data from a discrete mixed membership model

1 2	rmixedMem(Total, J, Rj = rep(1, J), Nijr = array(1, dim = c(Total, J, max(Rj))), K, Vj, dist, theta, alpha, lambda = NULL)

`Total`	the number of individuals in the sample.
`J`	the number of variables observed on each individual.
`Rj`	a vector of positive integers of length `J` specifying the number of repeated measurements for each variable.
`Nijr`	an array of dimension (`Total`, `J`, `max(Rj)`) indicating the number of ranking levels for each replication. For multinomial and Bernoulli variables, `Nijr`[i,j,r] = 1. For rank variables, `Nijr`[i,j,r] indicates the number of items ranked for each individual.
`K`	the number of latent sub-populations.
`Vj`	a vector of length `J` specifying the number of possible categories for each variable. For a Bernoulli variable `Vj`[j] = 1. For a multinomial or rank variable, `Vj`[j] is the number of possible categories/items.
`dist`	a vector of strings of length `J` specifying variable types. Options are "bernoulli", "multinomial" or "rank" corresponing to the distributions of the observed variables.
`theta`	an 3 way array of dimensions (`J`,`K`,`max(Vj)`) which governs the variable distributions. Parameter `theta`[j,k,] governs the distirbution of responses on variable j for an inidvidually completely in sub-population k. If the number of items/categories differs across variables, any unusued portions of `theta` should be set to 0. @param lambda an optional matrix of dimensions (`Total`, `K`) containing the membership scores for each individual. If the `lambda` argument is not specified, the group membership scores will be automatically sampled from a Dirichlet(`alpha`)
`alpha`	a positive `K`-length vector which is the parameter for the Dirichlet distribution of membership scores.

rmixedMem simulates data from a mixed membership model given the specified parameters and dimensions. The function returns a random sample of observations obs, context indicators Z, and group membership scores lambda.

rmixedMem returns a list containing a three items: A matrix of group memberships scores lambda, an array of context indicators Z and an array of observations obs.

ysamwang/mixedMem documentation built on May 4, 2019, 5:33 p.m.