qqnorm | R Documentation |
Calculates a normal qq-plot for a vector of data along with 95 percent simultaneous confidence bands.
qqnorm(y, pch = 20, xlab = "Standard Normal Quantiles", ylab = "Sample Quantiles",
make.plot = TRUE, ...)
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. |
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).
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. |
Peter Guttorp, peter βatβ stat.washington.edu, modified by Eric Gilleland
Doksum, K. A. and G. L. Sievers, 1976. Plotting with confidence: graphical comparisons of two populations. Biometrika, 63 (3), 421β434.
qnorm
, qqplot
, shiftplot
z <- rexp(100)
qqnorm( z)
y <- rnorm( 100)
qqnorm( y)
obj <- qqnorm(y, make.plot=FALSE)
str(obj)
data( ftcanmax)
qqnorm( ftcanmax[,"Prec"])
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.