hanr_wavelet: Anomaly detector using Wavelet

In harbinger: A Unified Time Series Event Detection Framework

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),])

harbinger documentation built on June 22, 2024, 7:38 p.m.