wbs (version 1.4)

ssic.penalty: Strengthened Schwarz Information Criterion penalty term

Description

The function evaluates the penalty term for the strengthened Schwarz Information Criterion proposed in P. Fryzlewicz (2014). This routine is typically not called directly by the user; its name can be passed as an argument to changepoints.

Usage

ssic.penalty(n, cpt, alpha = 1.01, ssic.type = c("log", "power"))

Arguments

n

the number of observations

cpt

a vector with localisations of change-points

alpha

a scalar greater than one

ssic.type

a string ("log" or "power")

Value

the penalty term \(k(\log(n))^{alpha}\) for ssic.penalty="log" or \(k n^{alpha}\) for ssic.penalty="power", where \(k\) denotes the number of elements in cpt

References

P. Fryzlewicz (2014), Wild Binary Segmentation for multiple change-point detection. Annals of Statistics, to appear. (http://stats.lse.ac.uk/fryzlewicz/wbs/wbs.pdf)

Examples

# NOT RUN {
x <- rnorm(300) + c(rep(1,50),rep(0,250))
w <- wbs(x)
w.cpt <- changepoints(w,penalty="ssic.penalty")
w.cpt$cpt.ic
# }