| GeneralizedHyperbolicPlots | R Documentation | 
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.
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, ...)
| y | The data sample. | 
| mu | 
 | 
| delta | 
 | 
| alpha | 
 | 
| beta | 
 | 
| lambda | 
 | 
| 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. | 
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. | 
Wilk, M. B. and Gnanadesikan, R. (1968) Probability plotting methods for the analysis of data. Biometrika. 55, 1–17.
ppoints, dghyp.
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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