qqgig function

Generalized Inverse Gaussian Quantile-Quantile and Percent-Percent Plots

qqgig produces a generalized inverse Gaussian QQ plot of the values in y.

ppgig produces a generalized inverse Gaussian PP (percent-percent) or probability plot of the values in y.

If line = TRUE, a line with zero intercept and unit slope is added to the plot.

Graphical parameters may be given as arguments to qqgig, and ppgig.

qqgig(y, chi = 1, psi = 1, lambda = 1,
      param = c(chi, psi, lambda),
      main = "GIG Q-Q Plot",
      xlab = "Theoretical Quantiles",
      ylab = "Sample Quantiles",
      plot.it = TRUE, line = TRUE, ...)

ppgig(y, chi = 1, psi = 1, lambda = 1,
      param = c(chi, psi, lambda),
      main = "GIG P-P Plot",
      xlab = "Uniform Quantiles",
      ylab = "Probability-integral-transformed Data",
      plot.it = TRUE, line = TRUE, ...)

Arguments

• y: The data sample.
• chi: A shape parameter that by default holds a value of 1.
• psi: Another shape parameter that is set to 1 by default.
• lambda: Shape parameter of the GIG distribution. Common to all forms of parameterization. By default this is set to 1.
• param: Parameters of the generalized inverse Gaussian distribution.
• xlab, ylab, main: Plot labels.
• plot.it: Logical. TRUE denotes the results should be plotted.
• line: Logical. If TRUE, a line with zero intercept and unit slope is added to the plot.
• ...: Further graphical parameters.

Returns

For qqgig and ppgig, a list with components: - x: The x coordinates of the points that are be plotted.

• y: The y coordinates of the points that are be plotted.

References

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

See Also

ppoints, dgig.

Examples

par(mfrow = c(1, 2))
y <- rgig(1000, param = c(2, 3, 1))
qqgig(y, param = c(2, 3, 1), line = FALSE)
abline(0, 1, col = 2)
ppgig(y, param = c(2, 3, 1))