GetBestBreak: Find most likely change point in irregular time series

Description Usage Arguments Value Author(s) See Also Examples

View source: R/GetBestBreak.R

Description

Finds the single best change point according to the likelihood function. Used internally within WindowSweep.

Usage

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GetBestBreak(x, t, range = 0.6, ...)

Arguments

x

vector of time series values.

t

vector of times of measurements associated with x.

range

tange of possible breaks. Default (0.6) runs approximately from 1/5th to 4/5ths of the total length of the time series.

...

additional parameters to pass to GetDoubleL function.

Value

returns a single row (vector) with elements: breaks,tbreaks,mu1,sigma1,rho1,LL1,mu2,sigma2,rho2,LL2,LL. The breakpoint is calculated for a range of possible values of width range*l (where l is the length of the time series). The output of this function feeds WindowSweep.

Author(s)

Eliezer Gurarie

See Also

WindowSweep which uses it, and GetDoubleL for the likelihood estimation.

Examples

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# An example with a single break:
x <- c(arima.sim(list(ar = 0.9), 20) + 10, arima.sim(list(ar = 0.1), 20))
t <- 1:length(x)
plot(t,x, type="l")
(bb <- GetBestBreak(x,t, tau=FALSE))
abline(v = bb[2], col=2)

Example output

Loading required package: Rcpp
Loading required package: plyr
   bb.index     bb.time         mu1          s1     rho.hat          LL 
 19.0000000  19.0000000   9.6188580   1.2285724   0.7542555 -21.6867431 
        mu2          s2     rho.hat          LL ll.total.LL 
  0.7589987   3.1878287   0.5735908 -46.3067067 -67.9934497 

bcpa documentation built on May 1, 2019, 10:30 p.m.