metRology (version 0.9-28-1)

boxplot.mandel.kh: Box plot of Mandel's h or k statistics

Description

Produces a box plot of Mandel's statistics, with optional outlier labels and indicator lines for unusual values.

Usage

# S3 method for mandel.kh
boxplot(x, probs=c(0.95, 0.99), main,  
		xlab=attr(x, "grouped.by"), ylab=attr(x, "mandel.type"),
		separators=FALSE, zero.line=TRUE, ylim,  p.adjust="none", 
		frame.plot = TRUE, horizontal=FALSE, at,
		... , 
		col.ind=1, lty.ind=c(2,1), lwd.ind=1, 
		col.sep="lightgrey", lwd.sep=1, lty.sep=1,
		lwd.zero=1, col.zero=1, lty.zero=1,
		outlier.labels=row.names(x), cex.lab=0.7, col.lab=1, 
		adj=NULL, pos=NULL, srt=0 )

Arguments

x

An object of class "mandel.kh"

probs

Indicator lines are drawn for these probabilities. Note that probs is interpreted as specifying two-tailed probabilities for Mandel's h and one-sided (upper tail) probabilities for Mandel's k.

main

a main title for the plot. If missing, the default is paste(deparse(substitute(x)), " - Mandel's", attr(x, "mandel.type"), if(attr(x, "mandel.method") == "robust") "(Robust variant)")

xlab

a label for the x axis; defaults to the grouped.by attribute for x.

ylab

a label for the x axis; defaults to the mandel.type attribute for x.

separators

Logical; if TRUE, separator lines are drawn between groups of values.

zero.line

logical; if TRUE a horizontal line is drawn at zero.

ylim

the y limits of the plot. For Mandel's k, the default lower limit for y is zero.

p.adjust

Correction method for probabilities. If not "none", passed to p.adjust prior to calculating indicator lines. Usually, indicator lines are drawn without correction (that is, with p.adjust="none"); specifying a p-value correction effectively turns the Mandel's statistics into single outlier tests.

frame.plot

Logical; If TRUE a box is drawn around the plot.

horizontal

if TRUE boxes are plotted horizontally and separators, indicators etc adjusted accordingly.

at

numeric vector giving the locations where the boxplots should be drawn; defaults to 1:n where n is the number of boxes.

…

Other (usually graphical) parameters passed to barplot. Note that some parameters appear after … to prevent spurious argument matching inside barplot.default.

col.ind, lty.ind, lwd.ind

Graphical parameters used for the indicator lines, recyckled to length(probs). For attr(x, "mandel.type")=="h" the graphical parameters are applied to negative as well as positive indicator lines, applied outwards from zero.

col.sep, lwd.sep, lty.sep

Graphical parameters used for the separator lines.

lwd.zero, col.zero, lty.zero

Graphical parameters used for the zero line.

outlier.labels

Either a logical indicating whether outliers should be labelled or a character vector of length nrow(x) giving labels. Defaults to row.names(x).

cex.lab, col.lab

Character size and colour for outlier labels, passed to text as col and cex respectively.

adj, pos

Position of outlier labels relative to outliers; passed to text.

srt

Label rotation, in degrees, for outlier labels; passed to text.

Value

boxplot.mandel.kh returns the box plot statistics returned by boxplot, invisibly.

Details

This plot produces a box plot (using boxplot.default) of the variables in an object of class "mandel.kh".

If labels are specified for outliers (the default), outliers are first located based on the locations given by boxplot.default. WARNING: ties may be mislabelled, as the label allocated will be the _first_ point at that location.

Indicator lines are, if requested, drawn as for plot.mandel.kh.

Vertical separators are drawn at midpoints of at. If

See Also

boxplot for box plot arguments, and text for outlier label location, colour and rotation. mandel.h, mandel.k, mandel.kh, pmandelh, pmandelk for probabilities, quantiles etc.

See plot.mandel.kh for the 'classic' Mandel plot.

Examples

# NOT RUN {
   data(RMstudy)

   h <- with(RMstudy, mandel.h(RMstudy[2:9], g=Lab))
   boxplot(h, las=2) 
   	#Recall that for normally distributed data mandel's h should 
   	#have the same dispersion (and IQR) for all groups. But outliers adversely 
   	#affect the estimate of dispersion, so the interquartile ranges differ.
   	#The same effect also accounts for the many boxplot outliers visible
   	#inside the classical Mandel indicator lines; the indicators also 
   	#assume normality.
   	
   #with separators:
   boxplot(h, las=2, separators=TRUE)
   
   #With different labels and label colours:
   boxplot(h, las=2, outlier.labels=paste(1:nrow(h)), col.lab=1:5) 
   
   #... and a horizontal variant (note use of pos to change label positions)
   par(omd=c(0.1,1,0,1))		#to make room for axis labels
   boxplot(h, las=1, separators=TRUE, horizontal=TRUE, pos=1)

# }