StructuredAdditiveTerm.summarise_by_samples()

StructuredAdditiveTerm.summarise_by_samples()#

StructuredAdditiveTerm.summarise_by_samples(key, samples, n=100, x=None, center=False, scale=False)[source]#

Computes a posterior summary for this term based on a subsample from the posterior.

Parameters:

  • key (Any) – A jax.random.PRNGKey for reproducibility.

  • samples (dict[str, Any]) – Array of posterior samples.

  • n (int) – The number of samples to draw. (default: 100)

  • x (Optional[Any]) – Array of covariate values. (default: None)

  • center (bool) – Whether to center the predictions. (default: False)

  • scale (bool) – Whether to scale the predictions. (default: False)

  • indices – If not None, only the columns of x with these indices are used.

Return type:

DataFrame

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