summarise_cluster()#

liesel_gam.summarise_cluster(term, samples, newdata=None, labels=None, quantiles=(0.05, 0.5, 0.95), hdi_prob=0.9)[source]#

Summarises a discrete term represented by RITerm or MRFTerm.

Parameters:

term (RITerm | MRFTerm | StrctTerm) – The term to summarise.
samples (Mapping[str, Array | ndarray | bool | number | bool | int | float | complex]) – Dictionary of posterior samples. Must contain samples for the term’s coefficient.
newdata (Position (dict[str, Any]) | None | Mapping[str, Array | ndarray | bool | number | bool | int | float | complex | Sequence[int] | Sequence[str]], default: None) – Dictionary of covariate data at which to summarise the term. If None, uses the unique clusters known to the term.
labels (CategoryMapping | Sequence[str] | None, default: None) – Custom mapping to use for mapping between string labels and integer codes.
quantiles (Sequence[float], default: (0.05, 0.5, 0.95)) – Probability levels of quantiles to include.
hdi_prob (float, default: 0.9) – Probability level for highest posterior density interval.

Return type:

DataFrame

summarise_cluster()