qqnorm {stats} R Documentation

Quantile-Quantile Plots

Description

qqnorm is a generic function the default method of which produces a normal QQ plot of the values in y. qqline adds a line to a “theoretical”, by default normal, quantile-quantile plot which passes through the probs quantiles, by default the first and third quartiles.

qqplot produces a QQ plot of two datasets.

Graphical parameters may be given as arguments to qqnorm, qqplot and qqline.

Usage

qqnorm(y, ...)
## Default S3 method:
qqnorm(y, ylim, main = "Normal Q-Q Plot",
xlab = "Theoretical Quantiles", ylab = "Sample Quantiles",
plot.it = TRUE, datax = FALSE, ...)

qqline(y, datax = FALSE, distribution = qnorm,
probs = c(0.25, 0.75), qtype = 7, ...)

qqplot(x, y, plot.it = TRUE,
xlab = deparse1(substitute(x)),
ylab = deparse1(substitute(y)), ...)


Arguments

 x The first sample for qqplot. y The second or only data sample. xlab, ylab, main plot labels. The xlab and ylab refer to the y and x axes respectively if datax = TRUE. plot.it logical. Should the result be plotted? datax logical. Should data values be on the x-axis? distribution quantile function for reference theoretical distribution. probs numeric vector of length two, representing probabilities. Corresponding quantile pairs define the line drawn. qtype the type of quantile computation used in quantile. ylim, ... graphical parameters.

Value

For qqnorm and qqplot, a list with components

 x The x coordinates of the points that were/would be plotted y The original y vector, i.e., the corresponding y coordinates including NAs.

References

Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole.

ppoints, used by qqnorm to generate approximations to expected order statistics for a normal distribution.

Examples

require(graphics)

y <- rt(200, df = 5)
qqnorm(y); qqline(y, col = 2)
qqplot(y, rt(300, df = 5))

qqnorm(precip, ylab = "Precipitation [in/yr] for 70 US cities")

## "QQ-Chisquare" : --------------------------
y <- rchisq(500, df = 3)
## Q-Q plot for Chi^2 data against true theoretical distribution:
qqplot(qchisq(ppoints(500), df = 3), y,
main = expression("Q-Q plot for" ~~ {chi^2}[nu == 3]))
qqline(y, distribution = function(p) qchisq(p, df = 3),
probs = c(0.1, 0.6), col = 2)
mtext("qqline(*, dist = qchisq(., df=3), prob = c(0.1, 0.6))")
## (Note that the above uses ppoints() with a = 1/2, giving the
## probability points for quantile type 5: so theoretically, using
## qqline(qtype = 5) might be preferable.)


[Package stats version 4.2.2 Index]