Change-point detection is related to event/trend change detection. Seminal change point detects change points based on deviations of linear regression models adjusted with and without a central observation in each sliding window <10.1145/312129.312190>.
References
Ogasawara, E., Salles, R., Porto, F., Pacitti, E. Event Detection in Time Series. 1st ed. Cham: Springer Nature Switzerland, 2025. doi:10.1007/978-3-031-75941-3
Examples
library(daltoolbox)
# Load change-point example data
data(examples_changepoints)
# Use a simple example
dataset <- examples_changepoints$simple
head(dataset)
#> serie event
#> 1 0.00 FALSE
#> 2 0.25 FALSE
#> 3 0.50 FALSE
#> 4 0.75 FALSE
#> 5 1.00 FALSE
#> 6 1.25 FALSE
# Configure seminal change-point detector
model <- hcp_scp()
# Fit the model
model <- fit(model, dataset$serie)
# Run detection
detection <- detect(model, dataset$serie)
# Show detected change points
print(detection[(detection$event),])
#> idx event type
#> 50 50 TRUE changepoint