Hi, I have a binary target variable that I try to predict with using a Bernoulli likelihood and a Sigmoid function for the p of the likelihood like logistic regression. I am only interested in the probability of success. I have to say I am also quite new to Bayesian modelling and PyMC. I would li…

Updated solution after this topic How to perform weighted inference import numpy as np import pymc3 as pm import theano.tensor as T N = 1000 P = 0.2 data = np.zeros(N) data[:int(N * P)] = 1.0 weights = np.ones(N) weights[:int(N * P)] = 4.0 with pm.Model() as model: p_ = pm.Normal('p_',…

How to model/deal with weighted binary outcomes

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junpenglao June 2, 2018, 7:48pm 8

The potential is a constant - it will not have any effect on the parameters. You need to express the potential as condition on mu1 to make it has an effect on mu1

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How to model/deal with weighted binary outcomes

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