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qqnl produces a normal Laplace Q-Q plot of the values in y.
qqnl
y
ppnl produces a normal Laplace P-P (percent-percent) or probability plot of the values in y.
ppnl
Graphical parameters may be given as arguments to qqnl, and ppnl.
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, …)
The data sample.
\(\mu\) is the location parameter. By default this is set to 0.
\(\sigma\) is the variance parameter of the distribution. A default value of 1 has been set.
\(\alpha\) is a skewness parameter, with a default value of 1.
\(\beta\) is a shape parameter, by default this is 1.
Parameters of the normal Laplace distribution.
Plot labels.
Logical. Should the result be plotted?
Add line through origin with unit slope.
Further graphical parameters.
For qqnl and ppnl, a list with components:
The x coordinates of the points that are to be plotted.
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, dnl, nlFit
ppoints
dnl
nlFit
# NOT RUN { 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) # }
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