plot.Cksegs.1d.dp {Ckmeans.1d.dp} | R Documentation |
Plot optimal univariate segmentation results returned from Cksegs.1d.dp
.
## S3 method for class 'Cksegs.1d.dp' plot(x, xlab=NULL, ylab=NULL, main=NULL, sub=NULL, col.clusters=NULL, ...)
x |
an object of class as returned by |
xlab |
a character string. The x-axis label for the plot. |
ylab |
a character string. The x-axis label for the plot. |
main |
a character string. The title for the plot. |
sub |
a character string. The subtitle for the plot. |
col.clusters |
a vector of colors, defined either by integers or by color names. If the length is shorter than the number of clusters, the colors will be reused. |
... |
arguments passed to |
The function plot.Cksegs.1d.dp
shows segments as horizontal lines from the univariate
segmentation results obtained from function Cksegs.1d.dp
. It uses different colors to indicate segments.
An object of class "Cksegs.1d.dp
" defined in Cksegs.1d.dp
.
Joe Song
Wang, H. and Song, M. (2011) Ckmeans.1d.dp: optimal k-means clustering in one dimension by dynamic programming. The R Journal 3(2), 29–33. Retrieved from https://journal.r-project.org/archive/2011-2/RJournal_2011-2_Wang+Song.pdf
# Example: clustering data generated from a Gaussian # mixture model of three components x <- c(rnorm(50, mean=-1, sd=0.3), rnorm(50, mean=1, sd=0.3), rnorm(50, mean=3, sd=0.3)) y <- x^3 res <- Cksegs.1d.dp(y, x=x) plot(res, lwd=2)