I find some difficulty in reshaping a 1-dimensional array (or vector, matrix) into a 1-dimensional array of vectors. Could you give some suggestion to improve below Rstan code?

Here, I’m sampling 4 variables (e.g. S1, S2, S3, S4) for a number of years (total no. of years = nyrs). Given each year, I first sample the mean (and hence the sum) of S1 to S4, which will be randomly split to assign the value of each variable S1 to S4. Please see below code for example.

To speed up the sampling, I used “vectorization” in the sampling statement and then transform via “map_rect”. My problem is that:

The 3rd argument of “mac_rect” requires the input as a 1-dimensional array of vectors. Very much appreciate if you could give some advice for solving this issue.

Thanks very much!

Data input is as follows:

stan_data <- list(

“num_K2” = 3,

“nyrs” = 43,

“maxTAR” = 4,

“LB_bin_2D” = cbind( seq(1, 129, 3), rep(3, 43) )

)

The RStan code is as follows:

```
functions {
vector split_sumTAR (vector raw_vec, vector meanTAR_vec, real[] nSi, int[] LB_bin) {
int n = LB_bin[2];
vector[n] seed_vec = segment(raw_vec, LB_bin[1], n);
return (nSi[1] * rep_vector(meanTAR_vec[1], n+1) .* ( append_row(seed_vec, 1.0) - append_row(0.0, seed_vec)) );
}
}
data {
int <lower=0> num_K2;
int <lower=0> nyrs;
int <lower=0> LB_bin_2D [nyrs, 2];
real <lower=0.0> maxTAR;
}
transformed data {
int <lower=0> n_relaTAR_raw = sum( rep_array(nyrs, num_K2) );
real nSi_2D [nyrs, 2] = rep_array(maxTAR, nyrs, 2);
real logis_mu_meanTAR_1D [nyrs] = rep_array(0.0, nyrs); // mu for meanTAR
real logis_sigma_meanTAR_1D [nyrs] = rep_array(1.0, nyrs); // sigma for meanTAR
vector[n_relaTAR_raw] logis_relaTAR_mu_vec = rep_vector(0.0, n_relaTAR_raw); // mu for relaTAR
vector[n_relaTAR_raw] logis_relaTAR_sigma_vec = rep_vector(1.0, n_relaTAR_raw); // sigma for relaTAR
}
parameters {
real meanTAR_1D [nyrs]; // logistic sampling: mean(annual TAR)
vector[n_relaTAR_raw] relaTAR_raw_vec; // logistic sampling: sum(rela_TAR) over 3 heterologous serotypes over each year
}
transformed parameters {
real<lower=0.0, upper=maxTAR> meanTAR_infer_1D [nyrs] = inv_logit( meanTAR_1D );
vector<lower=0.0, upper=maxTAR>[n_relaTAR_raw] TAR_Si_T_1Dvec = map_rect(
split_sumTAR,
relaTAR_raw_vec,
meanTAR_infer_1D, // error here
nSi_2D,
LB_bin_2D
);
}
model {
meanTAR_1D ~ logistic(logis_mu_meanTAR_1D, logis_sigma_meanTAR_1D);
relaTAR_raw_vec ~ logistic(logis_relaTAR_mu_vec, logis_relaTAR_sigma_vec);
}
```

After running this code, I got the following Error message:

```
SYNTAX ERROR, MESSAGE(S) FROM PARSER:
third argument to map_rect must be of type vector[] (array of vectors)
error in 'model1a002fb34210_test' at line 57, column 4
-------------------------------------------------
55: nSi_2D,
56: LB_bin_2D
57: );
^
58:
-------------------------------------------------
PARSER EXPECTED: ")"
Error in stanc(file = file, model_code = model_code, model_name = model_name, :
failed to parse Stan model 'test' due to the above error.
```