MixtureModel-class: An object for running MCMC simulations.
Description
BatchModel and MarginalModel both inherit from this class.
Slots
k- An integer value specifying the number of latent classes.
hyperparams- An object of class `Hyperparameters` used to specify the hyperparameters of the model.
theta- the means of each component and batch
sigma2- the variances of each component and batch
nu.0- the shape parameter for sigma2
sigma2.0- the rate parameter for sigma2
pi- mixture probabilities which are assumed to be the same for all batches
mu- overall mean
tau2- overall variance
data- the data for the simulation.
data.mean- the empirical means of the components
data.prec- the empirical precisions
z- latent variables
zfreq- table of latent variables
probz- n x k matrix of probabilities
logprior- log likelihood of prior: log(p(sigma2.0)p(nu.0)p(mu))
loglik- log likelihood: $\sum p_k \Phi(\theta_k, \sigma_k)$
mcmc.chains- an object of class 'McmcChains' to store MCMC samples
batch- a vector of the different batch numbers
batchElements- a vector labeling from which batch each observation came from
modes- the values of parameters from the iteration which maximizes log likelihood and log prior
mcmc.params- An object of class 'McmcParams'
.internal.constraint- Constraint on parameters. For internal use only.