Change-point detection method that focus on identify change points in mean/variance doi:10.2307/2529204. It wraps the BinSeg implementation available in the changepoint library.
Examples
library(daltoolbox)
#loading the example database
data(examples_changepoints)
#Using simple example
dataset <- examples_changepoints$simple
head(dataset)
#> serie event
#> 1 0.00 FALSE
#> 2 0.25 FALSE
#> 3 0.50 FALSE
#> 4 0.75 FALSE
#> 5 1.00 FALSE
#> 6 1.25 FALSE
# setting up change point method
model <- hcp_binseg()
# fitting the model
model <- fit(model, dataset$serie)
# execute the detection method
detection <- detect(model, dataset$serie)
#> Warning: The number of changepoints identified is Q, it is advised to increase Q to make sure changepoints have not been missed.
# filtering detected events
print(detection[(detection$event),])
#> idx event type
#> 19 19 TRUE changepoint
#> 85 85 TRUE changepoint