Hi, I’m trying to use Pymc3 to find the appropriate number of componements used to predict a time serie of concentrations called aCH and aCOH. These are two distincts PLS models. Each model can use between 1 and 20 number of components. The predictions are stored in an ndarray with the time series …

Yes using Metropolis could produce invalid proposal as described in the other post you mentioned, but using Categorical distribution seems to work: n = aCH_.eval().shape[1] with pm.Model() as basic_model: # Priors for unknown model parameters b1 = pm.Uniform('b1', lower=0.3, upper=0.5, test…

Indexing using a free random variable

Questions

charlotte.burki March 13, 2018, 12:38pm 6

Thanks, yes it works!

But there is no way to make it work using Metropolis?

Compounds steps

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Indexing using a free random variable

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