across_fip: The value that maximises the CUSUM statistic across all the...

In wbsts: Multiple Change-Point Detection for Nonstationary Time Series

Description

This function is an internal the non-randomized of multi_across_fip.

Usage

across_fip(X, tau, p, epp, p1, Ts)

Arguments

X	The wavelet periodogram.
Ts	The sample size of the series.
tau	The CUSUM threshold.
epp	A minimum adjustment for the bias present in E^{(i)}_{t,T}.
p	A scalar in (0.67,1]

Value

1	maximum cusum value
2	the location of a point with the maximum cusum value

Author(s)

K. Korkas and P. Fryzlewicz

References

K. Korkas and P. Fryzlewicz (2017), Multiple change-point detection for non-stationary time series using Wild Binary Segmentation. Statistica Sinica, 27, 287-311. (http://stats.lse.ac.uk/fryzlewicz/WBS_LSW/WBS_LSW.pdf)

Examples

 
cps=seq(from=1000,to=2000,by=200)
y=sim.pw.arma(N =3000,sd_u = c(1,1.5,1,1.5,1,1.5,1),
b.slope=rep(0.99,7),b.slope2 = rep(0.,7), mac = rep(0.,7),br.loc = cps)[[2]]
z=ews.trans(y,scales=c(11,9,8,7,6))
across_fip(X=z, tau=tau.fun(y), p=.75, epp=rep(32,5), p1=5, Ts=length(y))

wbsts documentation built on July 1, 2020, 5:23 p.m.