Description Usage Arguments Value Examples
View source: R/AM_mix_hyperparams.R
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)).
1 | AM_mix_hyperparams_multiber(a0, b0)
|
a0 |
The a0 hyperparameters. |
b0 |
The b0 hyperparameters. |
An AM_mix_hyperparams
object. This is a configuration list to be used as mix_kernel_hyperparams
argument for AM_mcmc_fit
.
1 |
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