Simulator for Multivariate Observed Data

Hello, I was wondering if it’s possible to utilize the simulator for two different observed data. I extend one of the examples to produce N x 2 observed data points.

# --------------------------------------------------------------------------- #

import numpy as np
import pymc as pm

# --------------------------------------------------------------------------- #
def normal_sim(rng, a, b, size=1000):
    return rng.normal(a, b, size=(size, 2))

def analyze():

    data = np.random.normal(loc=0, scale=1, size=(500, 2))

    with pm.Model() as basic_model:
        a = pm.Normal('a', mu=0, sigma=5)
        b = pm.HalfNormal('b', sigma=1)
        simulator = pm.Simulator(
            's', normal_sim,
            params=(a, b), sum_stat='sort', epsilon=1,
        idata = pm.sample_smc(chains=4)

if __name__ == '__main__':

You should be able to do that yes