Closed
Description
Currently the front page of the documentation page displays a code snippet to show how easy it is to use PyMC. Update this code snippet to PyMC version 4
import pymc3 as pm
X, y = linear_training_data()
with pm.Model() as linear_model:
weights = pm.Normal("weights", mu=0, sigma=1)
noise = pm.Gamma("noise", alpha=2, beta=1)
y_observed = pm.Normal(
"y_observed",
mu=X @ weights,
sigma=noise,
observed=y,
)
prior = pm.sample_prior_predictive()
posterior = pm.sample()
posterior_pred = pm.sample_posterior_predictive(posterior)