resid_ID: Calculate the residuals related to the estimated signal
In IDetect: Isolate-Detect Methodology for Multiple Change-Point Detection

Description Usage Arguments Value Author(s) Examples

This function returns the difference between x and the estimated signal with change-points at cpt. The input in the argument type_chg will indicate the type of changes in the signal.

1 2	resid_ID(x, cpt, type_chg = c("mean", "slope"), type_res = c("raw", "standardised"))

`x`	A numeric vector containing the data.
`cpt`	A positive integer vector with the locations of the change-points. If missing, the `ID` function is called internally to detect any change-points that might be present in `x`.
`type_chg`	A character string, which defines the type of the detected change-points. If type_chg = ``mean'', then the change-points represent the locations of changes in the mean of a piecewise-constant signal. If type_chg = ``slope'', then the change-points represent the locations of changes in the slope of a piecewise-linear and continuous signal.
`type_res`	A choice of ``raw'' and ``standardised'' residuals.

If type_res = ``raw'', the function returns the difference between the data and the estimated signal. If type_res = ``standardised'', then the function returns the difference between the data and the estimated signal, divided by the estimated standard deviation.

Andreas Anastasiou, a.anastasiou@lse.ac.uk

single.cpt.pcm <- c(rep(4,1000),rep(0,1000))
single.cpt.pcm.noise <- single.cpt.pcm + rnorm(2000)
cpt_detect <- ID(single.cpt.pcm.noise, contrast = "mean")

residuals_cpt_raw <- resid_ID(single.cpt.pcm.noise, cpt = cpt_detect$cpt, type_chg = "mean",
type_res = "raw")

residuals_cpt_stand. <- resid_ID(single.cpt.pcm.noise, cpt = cpt_detect$cpt, type_chg = "mean",
type_res = "standardised")

plot(residuals_cpt_raw)
plot(residuals_cpt_stand.)