Usage
rmixedMem(Total, J, Rj, Nijr, K, Vj, dist, theta, alpha, lambda = NULL)
Arguments
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 candidates
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.
alpha
a positive K-length vector which is the parameter for the Dirichlet
distribution of membership scores.
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)