initOutput {NestedCategBayesImpute}

Set the output structure for saving posterior samples of parameters.

Description

Set the output structure for saving posterior samples of parameters.

Usage

initOutput(data, hyper, mc)

Arguments

data

A list object including all the necessary data variables needed by the sampler.; output of the ⁠initData⁠ function.

hyper

Hyper parameters for priors.

mc

MCMC parameters.

Value

A list of output parameters to be saved.

alphaout

Vector of posterior samples for the concentration parameter in the Dirichlet process for the group-level latent classes.

betaout

Vector of posterior samples for the concentration parameter in the Dirichlet process for the individual-level latent classes. Currently, this is assumed to be the same within all group-level classes.

piout

Matrix of posterior samples for the vector of probabilities for the group-level latent classes.

omegaout

3D array of posterior samples for the matrix of probabilities for the group-level and individual-level latent class pairs.

nout

Vector of posterior samples for the total number of impossible households sampled.

extrasize

Matrix of posterior samples for the number of impossible households sampled, split by household size.

F_occupied

Vector of posterior samples for the number of occupied household-level latent classes.

S_occupied_max

Vector of posterior samples for the max number of occupied individual-level latent classes.

elapsed_time

Vector of time taken to run each iteration.

newphiout

3D array of posterior samples for the individual-level probabilities for each individual-level variable by each pair of group-level and individual-level latent classes.

lambdaout

A list of an array of posterior samples for the group-level probabilities for each group-level variable. Each array in the list is for each group-level variable.

Author(s)

Quanli Wang, Olanrewaju Akande