plot.SK: Plot SK objects

View source: R/plot.SK.R

plot.SKR Documentation

Plot SK objects

Description

S3 method to plot SK objects.

Usage

## S3 method for class 'SK'
plot(x,
     result         = TRUE,
     replicates     = TRUE,
     pch            = 19,
     col            = NULL,
     xlab           = NULL,
     ylab           = NULL,
     xlim           = NULL,
     ylim           = NULL,
     axisx          = TRUE,
     axisy          = TRUE,
     id.lab         = NULL,
     id.las         = 1,
     yl             = TRUE,
     yl.lty         = 3,
     yl.col         = 'gray',
     dispersion     = c('none','mm','sd','ci','cip'),
     d.lty          = 1,
     d.col          = 'black',
     title          = '', ...)

Arguments

x

A SK object.

result

The result of the test (letters) should be visible.

replicates

The number of replicates should be visible.

pch

A vector of plotting symbols or characters.

col

A vector of colors for the means representation.

xlab

A label for the ‘⁠x⁠’ axis.

ylab

A label for the ‘⁠y⁠’ axis.

xlim

The ‘⁠x⁠’ limits of the plot.

ylim

The ‘⁠y⁠’ limits of the plot.

axisx

Axis x? If ‘⁠TRUE⁠’ you must accept the default, otherwise, you must customize.

axisy

Axis y? If ‘⁠TRUE⁠’ you must accept the default, otherwise, you must customize.

id.lab

Factor level names at ‘⁠x⁠’ axis.

id.las

Factor level names written either horizontally or vertically.

yl

Horizontal (reference) line connecting the circle to the ‘⁠y⁠’ axis.

yl.lty

Line type of ‘⁠yl⁠’.

yl.col

Line color of ‘⁠yl⁠’.

dispersion

Vertical line through the circle (mean value) linking the minimum to the maximum of the factor level values corresponding to that mean value. Other options are: sd (standard deviation), ci (confidence interval), cip (pooled confidence interval) and none.

d.lty

Line type of dispersion.

d.col

A vector of colors for the line type of dispersion.

title

A title for the plot.

...

Optional plotting parameters.

Details

The plot.SK function is a S3 method to plot ‘⁠Scott and Knott⁠’ objetcs. It generates a serie of points (the means) and a vertical line showing the dispersion of the values corresponding to each group mean. The ci options is calculed utilizing each treatment variance as estimating of population variance. The cip options is calculed utilizing the means square error (MSE) as estimating of population variance.

Author(s)

Jose Claudio Faria (joseclaudio.faria@gmail.com)
Enio Jelihovschi (eniojelihovs@gmail.com)
Ivan Bezerra Allaman (ivanalaman@gmail.com)

References

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

See Also

plot

Examples

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

library(ScottKnott)
data(CRD2)

## From: formula
sk1 <- with(CRD2,
            SK(y ~ x,
               data=dfm,
               which='x'))

old.par <- par(mar=c(6, 3, 6, 2))
plot(sk1,
     id.las=2)

plot(sk1,
     yl=FALSE,
     disp='sd',
     id.las=2)

## From: aov
av <- with(CRD2,
           aov(y ~ x,
               data=dfm))
summary(av)

sk2 <- SK(x=av,
          which='x')
plot(sk2,
     disp='sd',
     yl=FALSE,
     id.las=2)

# From: lm
av_lm <- with(CRD2,
           lm(y ~ x,
              data=dfm))

sk3 <- SK(x=av_lm,
          which='x')

par(mfrow=c(2, 1))
plot(sk3,
     disp='ci',
     id.las=2,
     yl=FALSE)

plot(sk3,
     disp='cip',
     id.las=2,
     yl=FALSE)

par(mfrow=c(1, 1))
par(old.par)

ScottKnott documentation built on Aug. 31, 2023, 1:06 a.m.