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Problem combining GaussianRandomWalk and Weibull distribution #3584
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The beta parameter of the Weibull distribution has to be positive. But you are setting it to a As this is not a bug I will close this issue and I invite you to post this question in our discourse. |
Ok, thanks for the feedback, I'll bring up the topic there. One suggestion: if easily possible (given this information is available at that point), the error message in this case might be improved to something like |
WRT @romankarlstetter 's request for a better error message, it looks like that's there already. Did I miss someone adding this? Or is there something wrong that causes this to be missed (see following)? Finally, why is this only a warning, instead of an |
In |
Hi,
I have data that I want to model using a Weibull distribution. I want to model it such that the beta parameter changes "over time" (data is a time series). I'm trying to model that using a Gaussian random walk, see here:
Unfortunately, this does not really work, I get the following error
TypeError: 'float' object is not subscriptable
This is because of the following check in the Weibull distribution, I guess:
https://github.com/pymc-devs/pymc3/blob/37466665efec5907c918f59a68edb6b11bea2b9e/pymc3/distributions/continuous.py#L2866
I don't really understand what's happening here. Why is that check there and what is it used for?
Is is even possible to do what I'm trying to do or is there a conceptual problem with my model?
Thanks in advance,
Roman
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