ghyp (version 1.6.5)

hist-methods: 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 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, ...)

Value

No value is returned.

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.

Author

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)