hist-methods: Histogram for univariate generalized hyperbolic distributions

In ghyp: Generalized Hyperbolic Distribution and Its Special Cases

Histogram for univariate generalized hyperbolic distributions

Description

The function hist computes a histogram of the given data values and the univariate generalized hyperbolic distribution.

Usage

## 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, ...)

Arguments

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.

Value

No value is returned.

Author(s)

David Luethi

See Also

qqghyp, fit.ghypuv, hist, legend, plot, lines.

Examples

  data(smi.stocks)
  univariate.fit <- fit.ghypuv(data = smi.stocks[,"SMI"],
                               opt.pars = c(mu = FALSE, sigma = FALSE),
                               symmetric = TRUE)
  hist(univariate.fit)

ghyp documentation built on Aug. 21, 2023, 5:12 p.m.