cr.rand.max.inner.prod {wbsts} | R Documentation |
The value that maximises the random CUSUM statistic across all the scales
Description
The function finds the value which yields the maximum inner product with the input time series (CUSUM) located between 100(1-p)\%
and 100p\%
of their support across all the wavelet periodogram scales.
Usage
cr.rand.max.inner.prod(XX,Ts,C_i,epp,M = 0,Plot = FALSE,cstar=0.95)
Arguments
XX |
The wavelet periodogram. |
Ts |
The sample size of the series. |
C_i |
The CUSUM threshold. |
epp |
A minimum adjustment for the bias present in |
M |
Number of random CUSUM to be generated. |
Plot |
Plot the threhsold CUSUM statistics across the wavelet scales. |
cstar |
A scalar in (0.67,1] |
Value
1 |
Candidate change point |
2 |
The maximum CUSUM value |
3 |
The starting point |
4 |
The ending point |
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))
#out=cr.rand.max.inner.prod(z, Ts = length(y),C_i = tau.fun(y),
#epp = rep(32,5), M = 2000, cstar = 0.75, Plot = 1)
#abline(v=cps,col="red")