plot.segmentation {tilingArray} | R Documentation |
This function visualizes the result of findSegments
.
The user can choose whether he wants to specify the number of segments
or let be determined by the function (see details).
## S3 method for class 'segmentation': plot(x, nSegments = NULL, bcol = NULL, from=NULL, to=NULL, ...)
x |
object of class "segmentation" |
nSegments |
number of segments in the data; if
NULL , it is determined within the function (see details) |
bcol |
color(s) to use for segment borders; if NULL they
are taken to be the colors 2:nSegments |
from |
numeric, index of data point to start plot at; default
NULL means take the first one |
to |
numeric, index of last data point to plot; default
NULL means take all up to the last one |
... |
further graphical parameters passed on to
plot.default |
If nSegments
is not specified, it is taken to be that number,
at which the Residual Sum of Squares shows the largest decrease from
the previous one. (The RSS decreases steadily, so absolute minimum is
reached when nSegments
equals the number of observations.
This can only be done if confidence intervals have been computed for
at least one of the segmentations, using the function
confint.segmentation
.
If result is assigned, returns a list containing
breakp |
the breakpoints of the chosen or computed segmentation |
confInt |
the confidence intervals of those breakpoints |
Joern Toedling toedling@ebi.ac.uk
findSegments
, confint.segmentation
dat <- c(rnorm(10,0,1),rnorm(20,2,1), rnorm(5,0.5,0.5), rnorm(10,1,1), rnorm(20,2,1)) if (require("strucchange")){ segres <- findSegments(dat, maxcp=10, maxk=15, verbose=TRUE) segres <- confint(segres, 3:6) plot(segres) } else { segres <- findSegments(dat, maxcp=10, maxk=15, verbose=TRUE) plot(segres, 5) }