I have the mean and the standard deviation of my observed data; they are not samples. I would like to know if it is possible to define the observed variable in the `pm.MvNormal()`

as a distribution, because usually I would draw samples from the distribution I know and then feed the model. I thought something like this, but it did not work.

theta = pm.Normal.dist(mu = theta_vt[0], sigma = dist_vt[0])

phi = pm.Normal.dist(mu = phi_vt[0], sigma = dist_vt[1])

p_hat = np.stack((theta, phi))

with pm.Model() as pos_model:

.

.

.

joint_obs = pm.MvNormal(‘joint’, mu=mu, cov=cov, observed=p_hat)