hanr_wavelet {harbinger} | R Documentation |
Anomaly detector using Wavelet
Description
Anomaly detection using Wavelet The Wavelet model adjusts to the time series. Observations distant from the model are labeled as anomalies. It wraps the Wavelet model presented in the stats library.
Usage
hanr_wavelet(filter = "haar")
Arguments
filter |
Availables wavelet filters: haar, d4, la8, bl14, c6 |
Value
hanr_wavelet
object
Examples
library(daltoolbox)
#loading the example database
data(examples_anomalies)
#Using simple example
dataset <- examples_anomalies$simple
head(dataset)
# setting up time series fft detector
model <- hanr_wavelet()
# fitting the model
model <- fit(model, dataset$serie)
detection <- detect(model, dataset$serie)
# filtering detected events
print(detection[(detection$event),])
[Package harbinger version 1.0.787 Index]