Hello, I am using PyMC v5.11.0. I am interested in performing an inference on the variables a, b, and an ensemble of {c} and {d} variables. That is, 2N + 2 variables in total. I have a uniform prior on all variables, except the {c} ones. dimension_names = ['Dim ’ + str(i) for i in range(N)] with …

Thank you very much for the prompt reply! You were right that the custom plotting function was the problem. Now that I replaced it with plot_posterior, I can see that the posteriors are indeed different. However, that is only when I use cores=4. When I change to cores=1 with pm.sample(1, tune=100…

2N+2 parameter inference: sampling all parameters as one?

Questions v5

iavicenna March 27, 2024, 12:09pm 2

Can you provide the functions f,g,h or even better a full sample code with simulated data

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2N+2 parameter inference: sampling all parameters as one?

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