Chapter 3, Clustering example, creating model.

[djole]

I have a quick question about the
initialization of the model class in the Chapter 3, clustering example.
Why are observations not included in the
list of parameters in mc.Model?

#and to combine it with the observations:
observations = mc.Normal( "obs", center_i, tau_i, value = data, observed = True )

#below we create a model class
model = mc.Model( [p, assignment, taus, centers ] )

[CamDavidsonPilon]

It is a mistake, unfortunately. Although the MCMC probably runs fine (can you confirm?), it is best practice to include it in the Model class along with the other variables. Thanks for pointing this out @djole

[djole]

It runs fine and the graphs seem consistent.

If it's the same, how come PyMC knows the likelihood distribution?
Is it by checking child variables of the variables included in the model?

BTW, thanks for all the good work :)

[CamDavidsonPilon]

Yup looks good.

Is it by checking child variables of the variables included in the model?

is likely correct. Thanks for the contribution!