Anomalyscoresframe: Anomaly score computation for a set of distances

In AnomalyScore: Anomaly Scoring for Multivariate Time Series

Anomaly score computation for a set of distances

Description

Computes anomaly scores for a selection of different distances for a single dataset.

Usage

Anomalyscoresframe(unit, knn, measures, dparams)

Arguments

unit	A matrix representing a multivariate time series where each column is a univariate time series.
knn	number of nearest neighbors to consider for the anomaly scores
measures	vector with the indexes of the selected measures 1=Cort, 2=Wasserstein, 3=Mahalanobis, 4=Normalized Cort, 5=Coherence, 6=PDC, 7=CGCI,8=RGPDC, 9=PMIME, 10=mvLWS, 11=Band depth
dparams	a list where each element is a list with all the parameters necessary to compute the selected distances. If the distance does not need further parameters then define an empty list

Value

A dataframe with the names of series in unit as a column called "series" and the corresponding scores computed for each distance. The rank is ordered with respect to the first measure in the measures index vector

See Also

Guillermo Granados, and Idris Eckley. "Electricity Demand of Buildings Benchmarked via Regression Trees on Nearest Neighbors Anomaly Scores"

Examples

unit=matrix( rnorm(500), ncol=5  )
measures= c(1,5,11 ) # Cort, Coherence and Band depth
knn=3
dparams=list(
  list(k=2),
  list( span1=2, span2=2, period = 5),
  list( )
)
Anomalyscoresframe(unit, knn,measures, dparams)

AnomalyScore documentation built on April 4, 2025, 3:13 a.m.