# qqnorm: 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

 ``` 1 2 3 4 5 6 7 8 9 10 11 12``` ```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 `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.
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19``` ```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.) ```