SingleBatchModel-class: The 'SingleBatchModel' class

In CNPBayes: Bayesian mixture models for copy number polymorphisms

Description

Run marginal MCMC simulation

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

u

latent chi square variable for t-distribution

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: ∑ p_k Φ(θ_k, σ_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'

label_switch

length-one logical vector indicating whether label-switching occurs (possibly an overfit model)

.internal.constraint

Constraint on parameters. For internal use only.

CNPBayes documentation built on May 6, 2019, 4:06 a.m.