Comments (3)
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
from probabilistic-programming-and-bayesian-methods-for-hackers.
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 :)
from probabilistic-programming-and-bayesian-methods-for-hackers.
Yup looks good.
Is it by checking child variables of the variables included in the model?
is likely correct. Thanks for the contribution!
from probabilistic-programming-and-bayesian-methods-for-hackers.
Related Issues (20)
- definition of a continuous distribution in chap 1
- Bug in Ch6_priors_pymc3.ipynb
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- Bug in Chapter 1 Pyro Version: Exponential Distribution Input HOT 2
- Port book to PyMC 4.0 HOT 7
- Chapter2 -- error in plot_artificial_sms_dataset() function
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- Crack
- Chapter 6: Bayesian Multi-armed Bandits Code
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- Ch3.type error at Example: Unsupervised Clustering using a Mixture Model HOT 2
- `pandas_datareader` error in chapter 6 HOT 1
- Chapter 1: Bug in plotting prior & posterior probabilities due to giving lw a string as an input HOT 1
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