Hi, I had made a simple linear regression model that predicts the mean response ‘mu’ and the observed score with mean mu and standard deviation sigma, as follows: This model works fine without error with pm.Model() as batting_score_model: batting_score_model.add_coord('observations', np.arange…

Does it mean that some of my sigma estimates end up being negative and therefore throwing an error? Yes, that sounds like the problem. What about X_data, is it always strictly positive? In general I would recommend using a link function to keep a model on sigma positive, rather than specifying …

Sampling error y inf when adding sigma heteroskedastic modelling

Questions v5

ArnoSixer November 15, 2024, 1:32pm 12

True, I had actually tried an exponential function but it made by estimates so huge that it created another error, using softplus went smoothly.

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Sampling error y inf when adding sigma heteroskedastic modelling

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