I’m trying to code a model that, there are 90 input features, these 90 features can be divided into 13 mutually exclusive groups. Features from the same group will follow the same normal distribution for each subject. We will end up with 13 normal distributions for each subject. we use the mean of normal distributions as new features. This can be seen as a dimensional reduction which reduce 90 features to 13 features. We use these reduced 13 features to fit regression model with a continuious outcome. If we dont give the true groups of each feature, but only give the total number of groups, then the group parameter, which is a simplex vector with 13 elements represents the probabilities of this feature belongs to which groups, can be generated from a multinomial distribution for each of 90 features. How do we code this in stan?