qqnorm: Normal qq-plot with 95 Percent Simultaneous Confidence Bands

In extRemes: Extreme Value Analysis

Normal qq-plot with 95 Percent Simultaneous Confidence Bands

Description

Calculates a normal qq-plot for a vector of data along with 95 percent simultaneous confidence bands.

Usage

qqnorm(y, pch = 20, xlab = "Standard Normal Quantiles", ylab = "Sample Quantiles",
    make.plot = TRUE, ...)

Arguments

y	numeric vector of data.
pch	plot symbol to use.
xlab	Character string giving abscissa label.
ylab	Character string giving ordinate axis label.
make.plot	logical, should the plot be created (TRUE) or not (FALSE)?
...	optional arguments to the plot function.

Details

Confidence intervals are calculated using +/- k, where

k = 0.895 / (sqrt(n) * (1- 0.01 / sqrt(n) + 0.85/n))

Gives a 95 percent asymptotic band based on the Kolmogorov-Smirnov statistic (Doksum and Sievers, 1976).

Value

A data frame object is returned invisibly with components:

x,y	the data and standard normal quantiles, resp.
lower,upper	lower and upper 95 percent confidence bands.

Author(s)

Peter Guttorp, peter “at” stat.washington.edu, modified by Eric Gilleland

References

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

See Also

qnorm, qqplot, shiftplot

Examples

z <- rexp(100)
qqnorm( z)

y <- rnorm( 100)
qqnorm( y)
obj <- qqnorm(y, make.plot=FALSE)
str(obj)

data( ftcanmax)
qqnorm( ftcanmax[,"Prec"])

extRemes documentation built on Nov. 19, 2022, 1:07 a.m.