Quantile-comparison plots

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Description

Plots empirical quantiles of a variable against theoretical quantiles of a comparison distribution.

Usage

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qqfun(x, distribution="norm", ylab=deparse(substitute(x)),
      xlab=paste(distribution, "quantiles"), main=NULL, las=par("las"),
      envelope=.95, labels=FALSE, col=palette()[4], lcol=palette()[2],
      xlim=NULL, ylim=NULL, lwd=1, pch=1, bg=palette()[4], cex=.4,
      line=c("quartiles", "robust", "none"), ...)

Arguments

x

vector of numeric values.

distribution

root name of comparison distribution – e.g., norm for the normal distribution; t for the t-distribution.

ylab

label for vertical (empirical quantiles) axis.

xlab

label for horizontal (comparison quantiles) axis.

main

label for plot.

envelope

confidence level for point-wise confidence envelope, or FALSE for no envelope.

labels

vector of point labels for interactive point identification, or FALSE for no labels.

las

if 0, ticks labels are drawn parallel to the axis; set to 1 for horizontal labels (see par).

col

color for points; the default is the fourth entry in the current color palette (see palette and par).

lcol

color for lines; the default is the second entry as above.

xlim

the x limits (x1, x2) of the plot. Note that x1 > x2 is allowed and leads to a reversed axis.

ylim

the y limits of the plot

pch

plotting character for points; default is 1 (a circle, see par).

bg

background color of points

cex

factor for expanding the size of plotted symbols; the default is .4.

lwd

line width; default is 1 (see par). Confidence envelopes are drawn at half this line width.

line

"quartiles" to pass a line through the quartile-pairs, or "robust" for a robust-regression line; the latter uses the rlm function in the MASS package. Specifying line = "none" suppresses the line.

...

arguments such as df to be passed to the appropriate quantile function.

Details

Draws theoretical quantile-comparison plots for variables and for studentized residuals from a linear model. A comparison line is drawn on the plot either through the quartiles of the two distributions, or by robust regression.

Any distribution for which quantile and density functions exist in R (with prefixes q and d, respectively) may be used. Studentized residuals are plotted against the appropriate t-distribution.

This is adapted from qq.plot of package car with different values for points and lines, more options, more transparent code and examples in the current setting. Another similar but sophisticated function is qqmath of package lattice.

Value

NULL. These functions are used only for their side effect (to make a graph).

Author(s)

John Fox, Jing Hua Zhao

References

Davison, A. C. (2003) Statistical Models. Cambridge University Press.

Leemis, L. M., J. T. Mcqueston (2008) Univariate distribution relationships. The American Statistician 62:45-53

See Also

qqnorm, qqunif, gcontrol2

Examples

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## Not run: 
p <- runif(100)
alpha <- 1/log(10)
qqfun(p,dist="unif")
qqfun(-log10(p),dist="exp",rate=alpha,pch=21)

#library(car)
#qq.plot(p,dist="unif")
#qq.plot(-log10(p),dist="exp",rate=alpha)

#library(lattice)
#qqmath(~ -log10(p), distribution = function(p) qexp(p,rate=alpha))

## End(Not run)

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