# qqnl: Normal Laplace Quantile-Quantile and Percent-Percent Plots In NormalLaplace: The Normal Laplace Distribution

## Description

qqnl produces a normal Laplace Q-Q plot of the values in y.

ppnl produces a normal Laplace P-P (percent-percent) or probability plot of the values in y.

Graphical parameters may be given as arguments to qqnl, and ppnl.

## Usage

  1 2 3 4 5 6 7 8 9 10 11 12 qqnl(y, mu = 0, sigma = 1, alpha = 1, beta = 1, param = c(mu, sigma, alpha, beta), main = "Normal Laplace Q-Q Plot", xlab = "Theoretical Quantiles", ylab = "Sample Quantiles", plot.it = TRUE, line = TRUE, ...) ppnl(y, mu = 0, sigma = 1, alpha = 1, beta = 1, param = c(mu, sigma, alpha, beta), main = "Normal Laplace P-P Plot", xlab = "Uniform Quantiles", ylab = "Probability-integral-transformed Data", plot.it = TRUE, line = TRUE, ...) 

## Arguments

 y The data sample. mu mu is the location parameter. By default this is set to 0. sigma sigma is the variance parameter of the distribution. A default value of 1 has been set. alpha alpha is a skewness parameter, with a default value of 1. beta beta is a shape parameter, by default this is 1. param Parameters of the normal Laplace distribution. xlab, ylab, main Plot labels. plot.it Logical. Should the result be plotted? line Add line through origin with unit slope. ... Further graphical parameters.

## Value

For qqnl and ppnl, a list with components:

 x The x coordinates of the points that are to be plotted. y The y coordinates of the points that are to be plotted.

## References

Wilk, M. B. and Gnanadesikan, R. (1968) Probability plotting methods for the analysis of data. Biometrika. 55, 1–17.

ppoints, dnl, nlFit

## Examples

 1 2 3 4 5 6 par(mfrow = c(1, 2)) param <- c(2, 2, 1, 1) y <- rnl(200, param = param) qqnl(y, param = param, line = FALSE) abline(0, 1, col = 2) ppnl(y, param = param) 

### Example output Loading required package: DistributionUtils