Hi everyone,

I am trying to infer the parameters of a Lotka-Volterra equations using Pymc3. I was following this Stan example. Is there a working example of how to do similar thing in Pymc3? I can’t seem to find any. I did the following the code but it is not working

```
def rhs_ode(y, a, b, c, d, dt):
yprime = T.zeros_like(y)
yprime = T.set_subtensor(yprime[0], y[0] + dt * (a*y[0] - b*y[0]*y[1]))
yprime = T.set_subtensor(yprime[1], y[1] + dt * (-c*y[1] + d*y[0]*y[1]))
return yprime
#Model
LV_Model = pm.Model()
dt = t[1] - t[0]
with LV_Model:
#priors
alpha = pm.Normal('alpha', mu=1, sd=0.5)
gamma = pm.Normal('gamma', mu=1, sd=0.5)
beta = pm.Normal('beta', mu=0.05, sd=0.05)
delta = pm.Normal('delta', mu=0.05, sd=0.05)
sigma = pm.Lognormal('sigma', mu=-1, tau=1, shape=2)
dt = T.fscalar('dt')
steps = T.iscalar('steps')
#Initial Conditions
Z0 = pm.Lognormal('Z0', mu=np.log(10), tau=1, shape=2)
# Symbolic loop through Euler updates
xout, updates = theano.scan(fn= rhs_ode,
outputs_info=Z0,
non_sequences=[alpha, beta, gamma, delta, dt],
n_steps=steps)
simulation = theano.function(inputs= [Z0, alpha, beta, gamma, delta, dt, steps],
outputs=xout,
updates=updates,
allow_input_downcast=True)
Y_obs = pm.Lognormal('Y_obs', mu=simulation(Z0, alpha, beta, gamma, delta, dt, steps), tau=sigma,observed=data)
```

I get the following error

```
TypeError: ('Bad input argument to theano function with name "<ipython-input-30-cc4f13908e04>:48" at index 0(0-based)', 'Expected an array-like object, but found a Variable: maybe you are trying to call a function on a (possibly shared) variable instead of a numeric array?')
```

The problem is, I think, with how I use theano scan and its function, and variable types. How could I make this work?