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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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.
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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 ...
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