# qqnorm {stats}

Quantile-Quantile Plots
Package:
stats
Version:
R 3.0.2

### 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, ...)

## S3 method for class 'default':
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 = 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` 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.

### Values

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 `NA`s.

### 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),
prob = c(0.1, 0.6), col = 2)
mtext("qqline(*, dist = qchisq(., df=3), prob = c(0.1, 0.6))")```

Documentation reproduced from R 3.0.2. License: GPL-2.