plot.Ckmeans.1d.dp {Ckmeans.1d.dp} R Documentation

## Plot Optimal Univariate Clustering Results

### Description

Plot optimal univariate clustering results returned from `Ckmeans.1d.dp`.

### Usage

```## S3 method for class 'Ckmeans.1d.dp'
plot(x, xlab=NULL, ylab=NULL, main=NULL,
sub=NULL, col.clusters=NULL, ...)
## S3 method for class 'Ckmedian.1d.dp'
plot(x, xlab=NULL, ylab=NULL, main=NULL,
sub=NULL, col.clusters=NULL, ...)
```

### Arguments

 `x` an object of class as returned by `Ckmeans.1d.dp` or `Ckmedian.1d.dp`. `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 `plot` function in package graphics.

### Details

The functions `plot.Ckmeans.1d.dp` and `plot.Ckmedian.1d.dp` visualize the input data as sticks whose heights are the weights. They use different colors to indicate clusters.

### Value

An object of class "`Ckmeans.1d.dp`" or "`Ckmedian.1d.dp`" defined in `Ckmeans.1d.dp`.

Joe Song

### Examples

```# 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))

res <- Ckmeans.1d.dp(x)
plot(res)

y <- (rnorm(length(x)))^2
res <- Ckmeans.1d.dp(x, y=y)
plot(res)

res <- Ckmedian.1d.dp(x)
plot(res)
```

[Package Ckmeans.1d.dp version 4.3.3 Index]