# PredictionResult


Container returned by [GAM.predict()](GAM.md#whittaker.GAM.predict) for `type="response"` or `type="link"`.


Usage

``` python
PredictionResult(
    values,
    se,
    linear_predictor,
    lower=None,
    upper=None,
)
```


Bundles the point predictions together with their optional standard errors and interval bounds so that all quantities produced by a single `predict()` call travel together. Use [values](TermsPredictionResult.md#whittaker.TermsPredictionResult.values) for the predictions themselves; the other attributes are populated only when the corresponding arguments (`se=True`, `interval=...`) were requested.


## Attributes


`values: numpy.ndarray`  
Predicted values, shape `(n,)`. On the response scale (`mu`) when `type="response"`, or on the linear predictor scale (`eta`) when `type="link"`.

`se: numpy.ndarray or None`  
Standard errors of the linear predictor, shape `(n,)`. `None` unless `se=True` was passed to `predict()`.

`linear_predictor: numpy.ndarray`  
Predictions on the linear predictor scale, shape `(n,)`. Always populated, regardless of `type`, so that the response-scale mean can be recovered via the link function.

`lower: numpy.ndarray or None`  
Lower bound of the requested interval, on the same scale as [values](TermsPredictionResult.md#whittaker.TermsPredictionResult.values). `None` unless [interval](PosteriorPredictResult.md#whittaker.PosteriorPredictResult.interval) was set to `"confidence"`, `"prediction"`, or `"simultaneous"`.

`upper: numpy.ndarray or None`  
Upper bound of the requested interval, on the same scale as [values](TermsPredictionResult.md#whittaker.TermsPredictionResult.values). `None` unless [interval](PosteriorPredictResult.md#whittaker.PosteriorPredictResult.interval) was set.