hanr_wavelet {harbinger} | R Documentation |
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.
hanr_wavelet(filter = "haar")
filter |
Availables wavelet filters: haar, d4, la8, bl14, c6 |
hanr_wavelet
object
library(daltoolbox)
#loading the example database
data(har_examples)
#Using example 1
dataset <- har_examples$example1
head(dataset)
# setting up time series fft detector
model <- hanr_wavelet()
# fitting the model
model <- fit(model, dataset$serie)
detection <- detect(model, dataset$serie)
# filtering detected events
print(detection[(detection$event),])