Inference

Fitting methods beyond pm.sample: optimization-based point estimates (find_MAP), Gaussian approximations (Laplace, INLA), and fast variational methods (Pathfinder, DADVI). fit is a single entry point that dispatches to these by name.

fit(method, **kwargs)	Fit a model with an inference algorithm.
find_MAP([method, model, use_grad, ...])	Fit a PyMC model via maximum a posteriori (MAP) estimation using JAX and scipy.optimize.
fit_laplace([optimize_method, model, ...])	Create a Laplace (quadratic) approximation for a posterior distribution.
fit_pathfinder([model, num_paths, ...])	Fit Pathfinder variational inference (multi-path, PyMC/PyTensor backend).
fit_dadvi([model, n_fixed_draws, n_draws, ...])	Does inference using Deterministic ADVI (Automatic Differentiation Variational Inference), DADVI for short.
fit_INLA(x, Q[, minimizer_seed, model, ...])	Performs inference over a linear mixed model using Integrated Nested Laplace Approximations (INLA).