growthcode_v2=’

functions {

real[] logisticgrowth(real t,

```
real[] y,
real[] theta,
real[] x_r,
int[] x_i
) {
real dydt[x_i[1]];
for (i in 1:x_i[1]){
dydt[i] = theta[1] * y[i] * (1-y[i]/theta[2]);
}
return dydt;
```

}

}

data {

int<lower=1> T;

int<lower=1> n_days;

real y0[n_days];

real z[T,n_days];

real t0;

real ts[T];

}

transformed data {

real x_r[0];

int x_i[1];

x_i[1] = n_days;

}

parameters {

real<lower=0> theta[2];

real<lower=0> sigma;

}

model {

real y_hat[T,n_days];

theta ~ cauchy(0,2.5);

sigma ~ normal(0,0.01);

y_hat = integrate_ode_rk45(logisticgrowth, y0, t0, ts, theta, x_r, x_i);

for (t in 1:T) {

```
for (i in 1:n_days) {
z[t,i] ~ normal(y_hat[t,i], sigma);
}
```

}

}

generated quantities{

real y_pred[T,n_days];

real z_pred[T,n_days];

y_pred = integrate_ode_rk45(logisticgrowth, y0, t0, ts, theta, x_r, x_i );

for (t in 1:T) {

```
for(i in 1:n_days){
z_pred[t,i] = y_pred[t,i] + normal_rng(0,sigma);
}
```

}

}

’

mod_v2 = stan_model(model_name = ‘logistic_growth_stan’,model_code = growthcode_v2)

fit_logistic_growth ← sampling(mod_v2,

```
data = list (
n_days = n_days,
y0 = y0[1:n_days],
z = z[,1:n_days],
t0 = t0,
ts = ts
),
seed = 123,
chains = 4,
iter = 1000,
warmup = 500
```

)

Error in FUN(X[[i]], …) : Stan does not support NA (in y0) in data

failed to preprocess the data; sampling not done