sampling_inference
This reference covers the sampling algorithms and inference methods available in PyMC for posterior inference.
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# PyMC Sampling and Inference Methods
This reference covers the sampling algorithms and inference methods available in PyMC for posterior inference.
## MCMC Sampling Methods
### Primary Sampling Function
**`pm.sample(draws=1000, tune=1000, chains=4, **kwargs)`**
The main interface for MCMC sampling in PyMC.
**Key Parameters:**
- `draws`: Number of samples to draw per chain (default: 1000)
- `tune`: Number of tuning/warmup samples (default: 1000, discarded)
- `chains`: Number of parallel chains (default: 4)
- `cores`: Number of CPU cores to use (default: all available)
- `target_accept`:
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