Hi all,

I have `N=45`

measures of the air temperature made on fixed coordinates (`x`

,`y`

) and I would like to fit a 2D Gaussian Process.

The values are stored in a dataframe (named `measured`

) with three columns(`x`

, `y`

, `VALUE`

).

A snippet of my STAN code is :

```
data {
int<lower=1> N; //number of observation
vector[N] X[2]; //coordinates
vector[N] Y; //observation
...
}
parameters {
real<lower=0> rho;
real<lower=0> sigma;
real<lower=0> alpha;
...
}
model {
matrix[N, N] K = cov_exp_quad(X, alpha, rho);
....
```

The structure of the STAN model for the GP follows the manual.

But when I try to run the model:

```
fit = sampling(model1, data = list(N=nrow(measured), X= matrix(c(measured$xsc,measured$ysc), nrow= nrow(measured)), Y=measured$VALUE), iter=200)
```

I receive the error

trying deprecated constructor; please alert package maintainer

Error in new_CppObject_xp(fields$.module, fields$.pointer, …) :

no valid constructor available for the argument list

failed to create the sampler; sampling not done

I understood that the reason of the error is in the use of the matrix notation between R and STAN for the input argument of the `cov_exp_quad_function(...)`

What is the correct data structure?

Session info ------------------------------------------------------------------

setting value

version R version 3.4.2 (2017-09-28)

system x86_64, linux-gnu

ui X11

language

collate en_US.UTF-8

tz Europe/Rome

date 2018-01-09

Packages ----------------------------------------------------------------------

package * version date source

rstan * 2.17.2 2017-12-21 CRAN (R 3.4.2)

StanHeaders * 2.17.1 2017-12-20 CRAN (R 3.4.2)