Change-point detection is related to event/trend change detection. Change Finder ARIMA detects change points based on deviations relative to ARIMA model doi:10.1109/TKDE.2006.1599387. It wraps the ARIMA model presented in the forecast library.
Examples
library(daltoolbox)
#loading the example database
data(examples_changepoints)
#Using simple example
dataset <- examples_changepoints$simple
head(dataset)
#> serie event
#> 1 0.00 FALSE
#> 2 0.25 FALSE
#> 3 0.50 FALSE
#> 4 0.75 FALSE
#> 5 1.00 FALSE
#> 6 1.25 FALSE
# setting up change point method
model <- hcp_cf_arima()
# fitting the model
model <- fit(model, dataset$serie)
detection <- detect(model, dataset$serie)
# filtering detected events
print(detection[(detection$event),])
#> idx event type
#> 51 51 TRUE changepoint