| hist-methods {ghyp} | R Documentation |
The function hist computes a histogram of the given data values
and the univariate generalized hyperbolic distribution.
## S4 method for signature 'ghyp':
hist(x, data = ghyp.data(x), gaussian = TRUE,
log.hist = F, ylim = NULL, ghyp.col = 1, ghyp.lwd = 1,
ghyp.lty = "solid", col = 1, nclass = 30, plot.legend = TRUE,
location = if (log.hist) "bottom" else "topright", legend.cex = 1, ...)
x |
Usually a fitted univariate generalized hyperbolic distribution
of class mle.ghyp. Alternatively
an object of class ghyp and a data vector. |
data |
An object coercible to a vector. |
gaussian |
If TRUE the probability density of the normal distribution is plotted as a reference. |
log.hist |
If TRUE the logarithm of the histogramm is plotted. |
ylim |
The “y” limits of the plot. |
ghyp.col |
The color of the density of the generalized hyperbolic distribution. |
ghyp.lwd |
The line width of the density of the generalized hyperbolic distribution. |
ghyp.lty |
The line type of the density of the generalized hyperbolic distribution. |
col |
The color of the histogramm. |
nclass |
A single number giving the number of cells for the histogramm. |
plot.legend |
If TRUE a legend is drawn. |
location |
The location of the legend. See legend for possible values. |
legend.cex |
The character expansion of the legend. |
... |
Arguments passed to plot and qqghyp. |
No value is returned.
David Luethi
qqghyp, fit.ghypuv,
hist, legend, plot,
lines.
data(smi.stocks)
univariate.fit <- fit.ghypuv(data = smi.stocks[,"SMI"],
opt.pars = c(mu = FALSE, sigma = FALSE),
symmetric = TRUE)
hist(univariate.fit)