Normal inverse Gaussian Quantile-Quantile and Percent-Percent Plots
qqnig produces a normal inverse Gaussian Q-Q plot of the values in
y.
ppnig produces a normal inverse Gaussian P-P (percent-percent) or
probability plot of the values in y.
Graphical parameters may be given as arguments to qqnig,
and ppnig.
qqnig(y, mu = 0, delta = 1, alpha = 1, beta = 0,
param = c(mu, delta, alpha, beta),
main = "Normal inverse Gaussian Q-Q Plot",
xlab = "Theoretical Quantiles",
ylab = "Sample Quantiles",
plot.it = TRUE, line = TRUE, ...)
ppnig(y, mu = 0, delta = 1, alpha = 1, beta = 0,
param = c(mu, delta, alpha, beta),
main = "Normal inverse Gaussian P-P Plot",
xlab = "Uniform Quantiles",
ylab = "Probability-integral-transformed Data",
plot.it = TRUE, line = TRUE, ...)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. |
param |
Parameters of the normal inverse Gaussian 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 qqnig and ppnig, 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.
par(mfrow = c(1, 2)) param <- c(2, 2, 2, 1.5) y <- rnig(200, param = param) qqnig(y, param = param, line = FALSE) abline(0, 1, col = 2) ppnig(y, param = param)
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