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)).