PYMC3 chains fail when data values exceed 10,000+ (large standard deviations)

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If I had to guess, I would say you are probably running into floating point issues. You can try changing the default floating point precision as discussed here.

Alternatively, standardizing data is a fairly conventional approach and it alleviates all sorts of issues. Besides not having to worry too much about the numerical representations, it’s also often easier to specify reasonable priors because you automatically know what the basic distribution of all variables is (i.e., each has a mean of 0 and an SD of 1). If you later need coefficients in the native space, it does require a bit of algebra to un-transform things, but it’s typically not that big a deal.

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