# ConcurvityResult


Concurvity diagnostics for smooth terms.


Usage

``` python
ConcurvityResult(
    worst,
    observed,
    estimate,
    labels=list(),
    full=True,
)
```


Values range from 0 (no concurvity) to 1 (complete confounding). When `full=True`, each array has shape `(n_smooths,)` measuring each smooth against all other model terms combined. When `full=False`, each array has shape `(n_smooths, n_smooths)` with pairwise measures.


## Attributes


`worst: NDArray`  
Upper-bound concurvity: the maximum proportion of each smooth's basis space that lies in the space of the comparator.

`observed: NDArray`  
Concurvity of the actual fitted smooth function.

`estimate: NDArray`  
Concurvity based on the estimated smooth's squared norm relative to the null model.

`labels: list[str]`  
Smooth term labels in the same order as the array axes.

`full: bool`  
Whether this is a full (overall) or pairwise result.