Description Usage Arguments Value Author(s)

View source: R/detect-outliers.R

This function uses a trained model stored as an`trendbing_model_fit`

object
to derive the prediction interval (PI) for a given alpha threshold; it
classifies as outliers every data point falling outside the interval.

1 | ```
detect_outliers(data, model, alpha = 0.05, ...)
``` |

`data` |
a |

`model` |
a fitted model as |

`alpha` |
the alpha threshold to be used for prediction intervals, defaulting to 0.05, i.e. 95% prediction intervals are derived |

`...` |
additional arguments passed to the underlying model prediction function |

A `data.frame`

containing the original data, the mean model
predictions, the lower and upper bounds of the prediction interval, a
variable `outlier`

indicating which point is an outlier as a `logical`

, and
the `classification`

of data points as a `factor`

with values `normal`

for
points within the PI, `increase`

for outliers above the PI, and `decrease`

for outliers below the PI.

Thibaut Jombart, Dirk Schumacher

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