AM_mix_hyperparams_multiber: multivariate Bernoulli mixture hyperparameters (Latent Class...

Description Usage Arguments Value Examples

View source: R/AM_mix_hyperparams.R

Description

Generate a configuration object that defines the prior hyperparameters for a mixture of multivariate Bernoulli. If the dimension of the data is P, then the prior is a product of P independent Beta distributions, Beta(a_{0i},b_{0i}). Therefore, the vectors of hyperparameters, a0 and b0, are P-dimensional. Default is (a0= c(1,....,1),b0= c(1,....,1)).

Usage

1

Arguments

a0

The a0 hyperparameters.

b0

The b0 hyperparameters.

Value

An AM_mix_hyperparams object. This is a configuration list to be used as mix_kernel_hyperparams argument for AM_mcmc_fit.

Examples

1
AM_mix_hyperparams_multiber (a0= c(1,1,1,1),b0= c(1,1,1,1))

AntMAN documentation built on July 23, 2021, 5:08 p.m.