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not (version 1.6)

aic.penalty: 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, ...)

Value

The penalty term \(2 \times \code{n.param}\).

Arguments

n

The number of observations.

n.param

The number of parameters in the model for which the penalty is evaluated.

...

Not in use.

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

Run this code
#*** 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]]

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