boxplot.SK: Boxplot SK Objects

In jcfaria/ScottKnott: The ScottKnott Clustering Algorithm

Description

S3 method to plot SK objects.

Usage

## S3 method for class 'SK'
boxplot(x,
         mean.type   = c('line', 'point', 'none'),
         xlab        = NULL,
         mean.col    = 'gray',
         mean.pch    = 1,
         mean.lwd    = 1,
         mean.lty    = 1,
         args.legend = NULL, ...)

Arguments

x	A SK object.
mean.type	The type of mean must be ploted. O default is "line".
xlab	A label for the x axis.
mean.col	A vector of colors for the means representation.
mean.pch	A vector of plotting symbols or characters. Only if type are "point".
mean.lwd	Line width of mean.
mean.lty	Line type of mean. Only if type are "line".
args.legend	List of additional arguments to be passed to legend; The default is NULL.
...	Optional plotting parameters.

Details

The boxplot.SK function is a S3 method to plot SK objetcs. The difference to generic function is the Scott & Knott inference under frame and the plot of means within box.

Author(s)

José Cláudio Faria ([e-mail])
Enio Jelihovschi ([e-mail])
Ivan Bezerra Allaman ([e-mail])

References

Murrell, P. (2005) R Graphics. Chapman and Hall/CRC Press.

See Also

boxplot

Examples

##
## Examples: Completely Randomized Design (CRD)
## More details: demo(package='SK')
##

library(ScottKnott)
data(CRD1)

## From: formula
# Simple!
sk1 <- SK(y ~ x,
          data=CRD1$dfm,
          which='x')
boxplot(sk1)

# A little more elaborate!
boxplot(sk1,
        mean.lwd=1.3,
        mean.col='red')

# A little more! 
boxplot(sk1,
        mean.lwd=1.3,
        mean.lty=2,
        mean.col='red',
        args.legend=list(x='bottomleft'))

# With point type!
boxplot(sk1,
        mean.type='point')

boxplot(sk1,
        mean.type='point',
        mean.pch=19,
        cex=1.5,
        mean.col='red')

# With other point
boxplot(sk1,
        mean.type='point',
        mean.pch='+',
        cex=2,
        mean.col='blue',
        args.legend=list(x='bottomleft'))

jcfaria/ScottKnott documentation built on Nov. 1, 2020, 8:04 a.m.