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GeneralizedHyperbolic (version 0.8-6)

GeneralizedHyperbolicPlots: Generalized Hyperbolic Quantile-Quantile and Percent-Percent Plots

Description

qqghyp produces a generalized hyperbolic Q-Q plot of the values in y.

ppghyp produces a generalized hyperbolic P-P (percent-percent) or probability plot of the values in y.

Graphical parameters may be given as arguments to qqghyp, and ppghyp.

Usage

qqghyp(y, mu = 0, delta = 1, alpha = 1, beta = 0, lambda = 1,
       param = c(mu, delta, alpha, beta, lambda),
       main = "Generalized Hyperbolic Q-Q Plot",
       xlab = "Theoretical Quantiles",
       ylab = "Sample Quantiles",
       plot.it = TRUE, line = TRUE, ...)

ppghyp(y, mu = 0, delta = 1, alpha = 1, beta = 0, lambda = 1, param = c(mu, delta, alpha, beta, lambda), main = "Generalized Hyperbolic P-P Plot", xlab = "Uniform Quantiles", ylab = "Probability-integral-transformed Data", plot.it = TRUE, line = TRUE, ...)

Value

For qqghyp and ppghyp, 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.

Arguments

y

The data sample.

mu

\(\mu\) is the location parameter. By default this is set to 0.

delta

\(\delta\) is the scale parameter of the distribution. A default value of 1 has been set.

alpha

\(\alpha\) is the tail parameter, with a default value of 1.

beta

\(\beta\) is the skewness parameter, by default this is 0.

lambda

\(\lambda\) is the shape parameter and dictates the shape that the distribution shall take. Default value is 1.

param

Parameters of the generalized hyperbolic 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.

References

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

See Also

ppoints, dghyp.

Examples

Run this code
par(mfrow = c(1, 2))
y <- rghyp(200, param = c(2, 2, 2, 1, 2))
qqghyp(y, param = c(2, 2, 2, 1, 2), line = FALSE)
abline(0, 1, col = 2)
ppghyp(y, param = c(2, 2, 2, 1, 2))

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