I never observed this in previous versions so it may not be something specific to cmdstan 2.18. In my stan model I have: parameters {
matrix[5, 240] beta_first;
and
transformed parameters {
vector[N] alpha = calculate_alpha(beta_first);

After fitting the model with cmdstan2.18 I run in R:
fit <- read_stan_csv(csvfile)
la <- extract(fit, permuted = TRUE)
I get
dim(la$beta_first) = c(1000, 240, 5) where 1000 is # of iterations.
i.e., beta_first is transposed.

Then in R code I expose calculate_alpha and run
alpha <- calculate_alpha(t(beta_first[1, , ])) which gives the completely different results from la$alpha[1].

I am completely confused and will appreciate any insight. The stan model is attached. NNsigma.2.18.stan (1.5 KB)

I have no problem with transpose. Since alpha is calculated both in stan and R using calculate_alpha function I am pretty sure that calculation in R is not correct. I donâ€™t know what is wrong. In stan model I call it using:

where dim(stan.x) is 12600x240, la$bias_first is 1000x5, la$bias_output is 1000, la$beta_first is 1000x240x5, la$beta_output is 1000x5. Unfortunately alpha.stan[1] is not la$alpha[1, 1]. This one confuses me.

The labels are an rstan thing so Iâ€™m not sure. My preference would be to hide this from the user entirely and mask the â€śtransposeâ€ť but itâ€™s likely a backwards-compatibility thing for rstan2 at this point.