plot.MFT {MFT}

plot.MFT

Description

Plot method for class 'mft'.

Usage

## S3 method for class 'MFT'
plot(x, col = NULL, ylab1 = NULL, ylab2 = NULL,
  cex.legend = 1.2, cex.diamonds = 1.4, main = TRUE, plot.Q = TRUE,
  plot.M = TRUE, plot.h = TRUE, breaks = NULL, wid = NULL, ...)

Arguments

x

object of class MFT

col

"gray" or vector of colors of length(H). Colors for (G_ht) plot, default: NULL -> rainbow colors from blue to red

ylab1

character, ylab for 1. graphic

ylab2

character, ylab for 2. graphic

cex.legend

numeric, size of annotations in plot

cex.diamonds

numeric, size of diamonds that indicate change points

main

logical, indicates if title and subtitle are plotted

plot.Q

logical, indicates if rejection threshold Q is plotted

plot.M

logical, indicates if test statistic M is plotted

plot.h

logical, indicates if a legend for the window set H is plotted

breaks

integer, >0, number of breaks in rate histogram

wid

integer, >0, width of bars in variance histogram

...

additional parameters

Author(s)

Michael Messer, Stefan Albert, Solveig Plomer and Gaby Schneider

References

Michael Messer, Marietta Kirchner, Julia Schiemann, Jochen Roeper, Ralph Neininger and Gaby Schneider (2014). A multiple filter test for the detection of rate changes in renewal processes with varying variance. The Annals of Applied Statistics 8(4): 2027-67 <doi:10.1214/14-AOAS782>

See Also

MFT.rate, MFT.variance, MFT.mean, MFT.peaks, summary.MFT

Examples

# Rate change detection in Poisson process 
# with three change points (at t = 250, 600 and 680)
set.seed(0)
Phi1 <- runif(rpois(1,lambda=390),0,250)
Phi2 <- runif(rpois(1,lambda=380),250,600)
Phi3 <- runif(rpois(1,lambda=200),600,680)
Phi4 <- runif(rpois(1,lambda=400),680,1000)
Phi  <- sort(c(Phi1,Phi2,Phi3,Phi4)) 
mft  <- MFT.rate(Phi)
plot(mft)