hanr_histogram: Anomaly detector using histogram

In harbinger: A Unified Time Series Event Detection Framework

Anomaly detector using histogram

Description

Anomaly detector using histogram

Usage

hanr_histogram(density_threshold = 0.05)

Arguments

density_threshold

It is the minimum frequency for a bin to not be considered an anomaly. Default value is 5%.

Value

hanr_histogram object histogram based method to detect anomalies in time series. Bins with smaller amount of observations are considered anomalies. Values below first bin or above last bin are also considered anomalies.>.

Examples

library(daltoolbox)

#loading the example database
data(examples_anomalies)

#Using simple example
dataset <- examples_anomalies$simple
head(dataset)

# setting up time series regression model
model <- hanr_histogram()

# 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.