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extRemes (version 1.65)

qqplot: qq-plot Between Two Vectors of Data with 95 Percent Confidence Bands

Description

QQ-plot between two data vectors with 95 percent confidence bands based on the Kolmogorov-Smirnov statistic (Doksum and Sievers, 1976).

Usage

qqplot(x, y, pch = 20, xlab = "x Quantiles", ylab = "y Quantiles", regress = TRUE,
    make.plot = TRUE, ...)

## S3 method for class 'qqplot': plot(x, ...)

## S3 method for class 'qqplot': summary(object, ...)

Arguments

x
qqplot: numeric vector of length 'm' giving one data set.

plot method function: list object of class qqplot returned by qqplot.

object
list object of class qqplot returned by qqplot.
y
numeric vector of length 'n' giving the other data set.
pch
Plot character.
xlab
Character string giving the label for the abscissa axis.
ylab
Character string giving the label for the ordinate axis.
regress
logical, should a regression line be fit to the quantiles?
make.plot
logical, should the plot be created (TRUE) or not (FALSE)?
...
Other optional arguments to the plot function. Not used by summary method function.

Value

  • An object of class qqplot is invisibly returned by each function (in the case of the method functions, the object entered is simply returned invisibly). This is a list object with components:
  • callcalling string
  • nameslist object with components x and y giving the object names for the objects passed into x and y, resp.
  • regressionIf regress was TRUE, then this is the fitted regression object as returned by lm. Otherwise, this component is not included.
  • qdatadata frame with components: x and y giving the quantiles for x and y, resp., and lower and upper giving the lower and upper 95 percent confidence bands, resp.

Details

Plots the sorted (missing-values removed) 'x' values against the sorted, and interpolated (via the approxfun function from package stats), 'y' values. Confidence bands are about the sorted and interpolated 'y' values using +/- K/sqrt(M), where

K = 1.36

and

M = m*n / (m+n).

The plot method function does exactly the same thing as qqplot except that it does not need to do any calculations.

The summary method function merely displays the original call to the function unless a regression line was fit between the quantiles, in which case summary information is displayed for the regression (i.e., the summary method function for lm is run on the lm object).

References

Doksum, K.A. and G.L. Sievers, 1976. Plotting with confidence: graphical comparisons of two populations. Biometrika, 63 (3), 421--434.

See Also

approxfun, qqnorm, shiftplot

Examples

Run this code
z <- rnorm(100)
y <- rexp(100)
qqplot( z, y)
qqplot( y, z)

data( ftcanmax)
qqplot( ftcanmax[,"Prec"], z)
obj <- qqplot( ftcanmax[,"Prec"], y, make.plot=FALSE)
plot(obj)
summary(obj)

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