Questions tagged [mcmc]

Markov chain Monte Carlo (MCMC) methods are a class of algorithms for sampling from a probability distribution based on constructing a Markov chain that has the desired distribution as its equilibrium distribution. The state of the chain after a number of steps is then used as a sample of the desired distribution

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Specifically how does MCMC update posteriors?

I'm learning about MCMC as it relates to Bayesian networks. As far as I can tell, MCMC operates with rejection sampling, but also updates the posterior distribution of the target variable in the ...
Oliver Foster's user avatar
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Use of PYMC distribution.dist()

In pymc3 documentation, it specifies that the .dist() member for distribution allows the distribution to be used without a model for sampling and use of the logp functions e.g. ...
rocklegend's user avatar
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the probability distribution of dependent variables

There are three variables, X3 is a function of X1 and X2, ...
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Varying strength of prior for MCMC hierarchical linear model

I am training an MCMC model in using Pymc3. My aim is to build a series of linear regression models which will predict the time to unload a truck, based on the number of crates to unload. I have ...
Tom's user avatar
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PyMC3 do not converge

I'm trying to run a simple logistic regression on PyMC3. Here the code: ...
Vincenzo Lavorini's user avatar