adamethods: do_clean – R documentation

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do_clean

Cleaning outliers

Cleaning of the most remarkable outliers. This improves the performance of the archetypoid algorithm since it is not affected by spurious points.

do_clean(data, num_pts, range = 1.5, out_perc = 80)

`data`	Data frame with (temporal) points in the rows and observations in the columns.
`num_pts`	Number of temporal points.
`range`	Same parameter as in function `boxplot`. A value of 1.5 is enough to detect amplitude and shift outliers, while a value of 3 is needed to detect isolated outliers.
`out_perc`	Minimum number of temporal points (in percentage) to consider the observation as an outlier. Needed when `range=1.5`.

Numeric vector with the outliers.

Irene Epifanio

data(mtcars)
data <- mtcars
num_pts <- ncol(data)
do_clean(t(data), num_pts, 1.5, 80)

Archetypoid Algorithms and Anomaly Detection

v1.2.1

GPL (>= 2)

Authors

Guillermo Vinue, Irene Epifanio

Initial release

2020-08-04