qqghyp(object, data = ghyp.data(object), gaussian = T, line = T,
main = "Generalized Hyperbolic Q-Q Plot",
xlab = "Theoretical Quantiles", ylab = "Sample Quantiles",
ghyp.pch = 1, gauss.pch = 6, ghyp.lty = "solid",
gauss.lty = "dashed", ghyp.col = "black", gauss.col = "black",
plot.legend = T, location = "topleft", legend.cex = 0.8,
spline.points = 150, root.tol = .Machine$double.eps^0.5,
rel.tol = root.tol, abs.tol = root.tol^1.5, ...)
mle.ghyp
. Alternatively
an object of class
TRUE
a qq-plot of the normal distribution is plotted as a reference.TRUE
a line is fitted and drawn.TRUE
a legend is drawn.legend
for possible values.qghyp
.uniroot
.integrate
.integrate
.plot
.hist
, fit.ghypuv
, qghyp
,
plot
,
lines
data(smi.stocks)
smi <- fit.ghypuv(data = smi.stocks[, "Swiss.Re"])
qqghyp(smi, spline.points = 100)
Run the code above in your browser using DataLab