The module `numpyro.infer.MCMC.MCMC` is a part of the NumPyro library in Python that provides functionality for performing Markov Chain Monte Carlo (MCMC) sampling. MCMC is a popular method used in Bayesian inference to estimate the posterior distribution of model parameters. This module allows users to define a probabilistic model using the NumPyro language and then apply MCMC algorithms such as Hamiltonian Monte Carlo and No-U-Turn Sampler to sample from the posterior distribution. The `MCMC` class provides methods to run the sampling process, retrieve samples, and perform diagnostics to assess the convergence and quality of the sampling results. It offers flexibility and customization options for users to specify various tuning parameters and control the sampling process. Overall, the `numpyro.infer.MCMC.MCMC` module is a powerful tool for performing Bayesian inference using MCMC in Python.
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