I have been trying to estimate a model with significantly large number of parameters and hence am using cmdstanr to save the draws straight to csv file and not have memory issues. However, I am getting a strange error I have not enocuntered yet and am not sure how to resolve this:

I have checked the code but can’t seem to find any issues. Below is the model code:

```
data {
int<lower=0> N;//Number of observations
int<lower=1> J;//Number of predictors with random slope
int<lower=1> K;//Number of predictors with non-random slope
int<lower=1> L;//Number of customers/groups
int<lower=0,upper=1> y[N];//Binary response variable
int<lower=1,upper=L> ll[N];//Number of observations in groups
matrix[N,K] x1;
matrix[N,J] x2;
}
transformed data {
matrix[N, K] Q_ast1;
matrix[K, K] R_ast1;
matrix[K, K] R_ast_inverse1;
matrix[N, J] Q_ast2;
matrix[J, J] R_ast2;
matrix[J, J] R_ast_inverse2;
// thin and scale the QR decomposition for x1
Q_ast1 = qr_thin_Q(x1) * sqrt(N - 1);
R_ast1 = qr_thin_R(x1) / sqrt(N - 1);
R_ast_inverse1 = inverse(R_ast1);
// thin and scale the QR decomposition for x2
Q_ast2 = qr_thin_Q(x2) * sqrt(N - 1);
R_ast2 = qr_thin_R(x2) / sqrt(N - 1);
R_ast_inverse2 = inverse(R_ast2);
}
parameters {
vector[J] rbeta_mu; //mean of distribution of beta parameters
vector<lower=0>[J] rbeta_sigma; //variance of distribution of beta parameters
vector[J] zeta_raw[L]; //group-specific parameters beta
vector[K] zeta;
}
transformed parameters {
vector[J] rzeta[L];
for (l in 1:L)
rzeta[l] = rbeta_mu + rbeta_sigma .* zeta_raw[l]; // coefficients on x
}
model {
rbeta_mu ~ normal(0,5);
rbeta_sigma ~ cauchy(0,10);
zeta~normal(0,5);
for (l in 1:L)
zeta_raw[l] ~ normal(0,1);
for(n in 1:N)
y[n]~bernoulli_logit(Q_ast1[n] * zeta + Q_ast2[n] * rzeta[ll[n]]);
}
generated quantities {
vector[K] beta;
vector[K] rbeta[L];
vector[N] log_lik;
for(l in 1:L){
rbeta[l] = R_ast_inverse2 * rzeta[l]; // coefficients on x1
}
beta = R_ast_inverse1 * zeta; // coefficients on x
for (n in 1:N) {
log_lik[n] = bernoulli_logit_lpmf(y[n] | x1[n] * beta + x2[n] * rbeta[ll[n]]);
}
}
```

I greatly appreciate your help in this matter. Thank you !