I am trying to use PyStan to estimate parameters for an ODE model. As an exercise I have been following the Lotka-Volterra tutorial by Bob Carpenter: https://mc-stan.org/users/documentation/case-studies/lotka-volterra-predator-prey.html

After failing to compile my own attempt at Stan code, I have copy-and-pasted the example given in the tutorial but still get the following error:

‘ValueError: Failed to parse Stan model ‘anon_model_55a47a04c3ed33f2bf08c4bd5e3a9a36’. Error message:

PARSER FAILED TO PARSE INPUT COMPLETELY’

STOPPED AT LINE 2:

This is my code in Spyder

```
model = """
real[] dz_dt(real t, real[] z, real[] theta,
real[] x_r, int[] x_i) {
real u = z[1];
real v = z[2];
real alpha = theta[1];
real beta = theta[2];
real gamma = theta[3];
real delta = theta[4];
real du_dt = (alpha - beta * v) * u;
real dv_dt = (-gamma + delta * u) * v;
return { du_dt, dv_dt };
}
data {
int<lower = 0> N; // num measurements
real ts[N]; // measurement times > 0
real y_init[2]; // initial measured population
real<lower = 0> y[N, 2]; // measured population at measurement times
}
parameters {
real<lower = 0> theta[4]; // theta = { alpha, beta, gamma, delta }
real<lower = 0> z_init[2]; // initial population
real<lower = 0> sigma[2]; // error scale
}
transformed parameters {
real z[N, 2]
= integrate_ode_rk45(dz_dt, z_init, 0, ts, theta,
rep_array(0.0, 0), rep_array(0, 0),
1e-6, 1e-5, 1e3);
}
model {
theta[{1, 3}] ~ normal(1, 0.5);
theta[{2, 4}] ~ normal(0.05, 0.05);
sigma ~ lognormal(-1, 1);
z_init ~ lognormal(log(10), 1);
for (k in 1:2) {
y_init[k] ~ lognormal(log(z_init[k]), sigma[k]);
y[ , k] ~ lognormal(log(z[, k]), sigma[k]);
}
}
"""
sm = pystan.StanModel(model_code = model)
```

I am new to Stan, but cannot see any errors. Can anyone tell me what I’m doing wrong?