Maybe is a stupid question, but I was wondering if in principle this:
simplex[N] pi; observed[g] ~ normal(a[1,g]*pi + a[2,g]*pi + ... , sigma);
is equivalent, to this:
simplex[N] pi; observed[g] ~ normal(a[n,g]*pi[n], sigma); //with sigma that might potentially vary per "n"
I am trying to think what are the differences in what “the model sees”.
I am not sure how the R linear regression and support vector regression (svm) implement their cost functions.