tsEvaChangepts {RtsEva}

Change point detection in time series

Description

This function applies the PELT method for change point detection in a time series. It returns the mean and variance of the series segments between change points.

Usage

tsEvaChangepts(series, timeWindow, timeStamps)

Arguments

series

A numeric vector representing the time series.

timeWindow

An integer specifying the minimum length of segments.

timeStamps

A vector of timestamps corresponding to the series data points.

Value

A list containing:

trend

A numeric vector of the same length as series, with each segment between change points filled with its mean value

variance

A numeric vector of the same length as series, with each segment between change points filled with its variance

changepoints

A vector of timestamps at which change points were detected

Examples

timeAndSeries <- ArdecheStMartin
timeStamps <- ArdecheStMartin[,1]
series <- ArdecheStMartin[,2]
timeWindow <- 30*365 # 30 years
result <- tsEvaChangepts(series, timeWindow, timeStamps)
plot(timeAndSeries, type = "l")
lines(timeStamps,result$trend,col=2)
points(timeStamps[result$changepoints], result$trend[result$changepoints], col = "red")