aic.penalty: Akaike Information Criterion penalty

In not: Narrowest-Over-Threshold Change-Point Detection

Akaike Information Criterion penalty

Description

The function evaluates the penalty term for Akaike Information Criterion. This routine is typically not called directly by the user; its name can be passed as an argument to features.

Usage

aic.penalty(n, n.param, ...)

Arguments

n	The number of observations.
n.param	The number of parameters in the model for which the penalty is evaluated.
...	Not in use.

Value

The penalty term 2*n.param.

References

R. Baranowski, Y. Chen, and P. Fryzlewicz (2019). Narrowest-Over-Threshold Change-Point Detection. (http://stats.lse.ac.uk/fryzlewicz/not/not.pdf)

Examples

#*** a simple example how to use the AIC penalty
x <- rnorm(300) + c(rep(1,50),rep(0,250))
w <- not(x)
w.cpt <- features(w, penalty="aic")
w.cpt$cpt[[1]]

not documentation built on Feb. 16, 2023, 9:55 p.m.