I am trying to model a GEV distribution with the Annual Maxima Series, but couldn’t find any example or tutorial to do it with PyStan. Right now, I am just going with the traditional approach of defining a transition model and the MCMC Metropolis-Hastings; but it seems to be very slow. Any leads? Thanks in advance
See this previous article on it Reparameterizing GEV Distribution
Can you also share more detail or code what you have tried.
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Thanks Dirk. I am trying to fit a GEV and get return levels with Bayesian Parametric inference. I want to do it with PyStan, but couldn’t find any tutorials or examples to fit a GEV.
Here is the link to my code.
https://github.com/Dawar-812/Bayesian-Parametric-Inference/blob/main/Bayesian%20Parametric%20Inference-GEV%20Distribution.ipynb