Python numpyro.infer.MCMC is a module of the Numpyro library that provides tools for performing Markov Chain Monte Carlo (MCMC) inference algorithms. MCMC is a computational method used to estimate the posterior distribution of parameters given observed data. With numpyro.infer.MCMC, users can easily sample from the posterior distribution, compute summary statistics, and perform inference on complex models. This module includes various MCMC algorithms such as the popular Hamiltonian Monte Carlo (HMC) and the No-U-Turn Sampler (NUTS). It also supports parallel and distributed computing, making it efficient for large-scale problems. Overall, numpyro.infer.MCMC is a powerful tool for Bayesian inference and probabilistic programming in Python.
Python MCMC - 30 examples found. These are the top rated real world Python examples of numpyro.infer.MCMC extracted from open source projects. You can rate examples to help us improve the quality of examples.