dot-replaceOutliers: Replace outliers with rolling median

In MazamaScience/AirSensor: Process and Display Data from Air Quality Sensors

Replace outliers with rolling median

Description

Perform smoothing by replacing outliers with the window median value. Using this technique, you can create an highly smoothed, artificial dataset by setting thresholdMin = 1 or lower (but always above zero).

Usage

.replaceOutliers(df = NULL, parameter = NULL, medWin = 7, ...)

Arguments

df	A data frame.
parameter	The data frame parameter to check and replace outliers.
medWin	The size of the rolling median window.
...	Parameters to extend flagOutliers.

Value

A data.frame with replaced outliers

MazamaScience/AirSensor documentation built on April 28, 2023, 11:16 a.m.