% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/hcp_scp.R
\name{hcp_scp}
\alias{hcp_scp}
\title{Seminal change point}
\usage{
hcp_scp(sw_size = 30)
}
\arguments{
\item{sw_size}{Sliding window size.}
}
\value{
\code{hcp_scp} object
}
\description{
Window-based change-point detection that compares two local linear models
fitted on each sliding window: one using the full window and another using the
same window split around its central observation. The difference between the
two residual summaries is used as the change score.

The method is called "seminal" because the paper defines a seminal point for
each window family, i.e. the central observation used to split the local
regression into two sides. This makes the detector a local family method based
on windows rather than a global segmentation algorithm.
}
\examples{
library(daltoolbox)

# Load change-point example data
data(examples_changepoints)

# Use a simple example
dataset <- examples_changepoints$simple
head(dataset)

# Configure the 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),])

}
\references{
\itemize{
\item The seminal change-point paper referenced in
\verb{Event Detection from Time Series Data}.
\item 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
}
}
