functional.draw_posterior()

Draw num_samples posterior samples of the latent sites from a fit.

Usage

Source

functional.draw_posterior(
    rng_key,
    fit,
    num_samples,
)

Dispatches on the fit type (e.g. SVIFit, MCMCFit). The returned dict has the sample axis leading and is ready to pass to forecast() or NumPyro’s Predictive.

Parameters

rng_key: Array

PRNG key.

fit: object

A fit result produced by fit_svi() or fit_mcmc().

num_samples: int

Number of posterior draws.

Returns

dict[str, Array]

Posterior samples of the latent sites, sample axis leading.

Raises

NotImplementedError

If fit is of an unsupported type.

Notes

For an MCMCFit, when num_samples does not exceed the number of draws in the chain the draws are thinned on an evenly spaced grid (no duplicates); only when more samples are requested than the chain holds are they resampled with replacement. For an SVIFit the draws are sampled afresh from the fitted guide.