qqnorm
QuantileQuantile Plots
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, quantilequantile 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
.
 Keywords
 hplot, distribution
Usage
qqnorm(y, ...)
"qqnorm"(y, ylim, main = "Normal QQ 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 = deparse(substitute(x)), ylab = deparse(substitute(y)), ...)
Arguments
 x
 The first sample for
qqplot
.  y
 The second or only data sample.
 xlab, ylab, main
 plot labels. The
xlab
andylab
refer to the y and x axes respectively ifdatax = TRUE
.  plot.it
 logical. Should the result be plotted?
 datax
 logical. Should data values be on the xaxis?
 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 inquantile
.  ylim, ...
 graphical parameters.
Value

For
 x
 The x coordinates of the points that were/would be plotted
 y
 The original
y
vector, i.e., the corresponding y coordinates includingNA
s.
qqnorm
and qqplot
, a list with components
References
Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole.
See Also
ppoints
, used by qqnorm
to generate
approximations to expected order statistics for a normal distribution.
Examples
library(stats)
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")
## "QQChisquare" : 
y < rchisq(500, df = 3)
## QQ plot for Chi^2 data against true theoretical distribution:
qqplot(qchisq(ppoints(500), df = 3), y,
main = expression("QQ plot for" ~~ {chi^2}[nu == 3]))
qqline(y, distribution = function(p) qchisq(p, df = 3),
prob = c(0.1, 0.6), col = 2)
mtext("qqline(*, dist = qchisq(., df=3), prob = c(0.1, 0.6))")
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