Chain 1 failed due to Mass matrix contains zeros on the diagonal

Questions
1

I ran into below error

Traceback (most recent call last):
File “C:\Users\chigozie.boniface_in\anaconda3\envs\downgrade\lib\site-packages\pymc3\parallel_sampling.py”, line 137, in run
self._start_loop()
File “C:\Users\chigozie.boniface_in\anaconda3\envs\downgrade\lib\site-packages\pymc3\parallel_sampling.py”, line 191, in _start_loop
point, stats = self._compute_point()
File “C:\Users\chigozie.boniface_in\anaconda3\envs\downgrade\lib\site-packages\pymc3\parallel_sampling.py”, line 216, in _compute_point
point, stats = self._step_method.step(self._point)
File “C:\Users\chigozie.boniface_in\anaconda3\envs\downgrade\lib\site-packages\pymc3\step_methods\arraystep.py”, line 276, in step
apoint, stats = self.astep(array)
File “C:\Users\chigozie.boniface_in\anaconda3\envs\downgrade\lib\site-packages\pymc3\step_methods\hmc\base_hmc.py”, line 147, in astep
self.potential.raise_ok(self._logp_dlogp_func._ordering.vmap)
File “C:\Users\chigozie.boniface_in\anaconda3\envs\downgrade\lib\site-packages\pymc3\step_methods\hmc\quadpotential.py”, line 272, in raise_ok
raise ValueError("\n".join(errmsg))
ValueError: Mass matrix contains zeros on the diagonal
The derivative of RV base_log__.ravel()[0] is zero.
The derivative of RV sat_paid_search_s_log__.ravel()[0] is zero.
The derivative of RV coef_paid_search_s_log__.ravel()[0] is zero.
The derivative of RV car_radio_s_logodds__.ravel()[0] is zero.
The derivative of RV sat_radio_s_log__.ravel()[0] is zero.
The derivative of RV coef_radio_s_log__.ravel()[0] is zero.
The derivative of RV car_tv_s_logodds__.ravel()[0] is zero.
The derivative of RV sat_tv_s_log__.ravel()[0] is zero.
The derivative of RV coef_tv_s_log__.ravel()[0] is zero.
“”"
while running

with pm.Model() as mmm:
channel_contributions = []

for channel in X.columns:
	coef = pm.Exponential(f'coef_{channel}', lam=0.0001) # regression coefficient
	sat = pm.Exponential(f'sat_{channel}', lam=1) # saturation strength
	car = pm.Beta(f'car_{channel}', alpha=2, beta=2) # carryover strength

	channel_data = X[channel].values
	channel_contribution = pm.Deterministic(f'contribution_{channel}',
											coef*saturate(carryover(channel_data, car), sat))
	channel_contributions.append(channel_contribution)

base = pm.Exponential('base', lam=0.0001) # baseline
noise = pm.Exponential('noise', lam=0.0001) # noise

sales = pm.Normal('revenue', mu=sum(channel_contributions) + base, sigma=noise, observed=y.values)
trace = pm.sample(return_inferencedata=True, tune=3000)

Kingly assist. I have gone through every suggestion regarding this error but couldn’t solve it.

2

Welcome!

How far into sampling did you get before this error occurred? If it occurred before the first sample, you might try:

trace = pm.sample(init='adapt_diag',
                  return_inferencedata=True,
                  tune=3000)

The jittering in default initialization (‘jitter+adapt_diag’) can throw errors when dealing with very small values (e.g., lam=0.0001).

1 Like
3

image
image1090×401 26.2 KB

But I replaced init=‘adapt_diag’ with init=‘map’ and it work but cann’t really differentiate the two.

4

From the documentation:

map: Use the MAP as starting point. This is discouraged.