swh:1:snp:d1587d616651317fdcebcbb237dce82c32266449
Tip revision: dfe6577bb164f53feaedf2da9530457197edfb1a authored by Georgi N. Boshnakov on 20 October 2022, 11:25:10 UTC
version 4021.93
version 4021.93
Tip revision: dfe6577
dist-ght.Rd
\name{ght}
\alias{dght}
\alias{pght}
\alias{qght}
\alias{rght}
\title{Generalized Hyperbolic Student-t}
\description{
Density, distribution function, quantile function
and random generation for the hyperbolic distribution.
}
\usage{
dght(x, beta = 0.1, delta = 1, mu = 0, nu = 10, log = FALSE)
pght(q, beta = 0.1, delta = 1, mu = 0, nu = 10)
qght(p, beta = 0.1, delta = 1, mu = 0, nu = 10)
rght(n, beta = 0.1, delta = 1, mu = 0, nu = 10)
}
\arguments{
\item{beta, delta, mu}{
numeric values.
\code{beta} is the skewness parameter in the range \code{(0, alpha)};
\code{delta} is the scale parameter, must be zero or positive;
\code{mu} is the location parameter, by default 0.
These are the parameters in the first parameterization.
}
\item{nu}{
a numeric value, the number of degrees of freedom.
Note, \code{alpha} takes the limit of \code{abs(beta)},
and \code{lambda=-nu/2}.
}
\item{x, q}{
a numeric vector of quantiles.
}
\item{p}{
a numeric vector of probabilities.
}
\item{n}{
number of observations.
}
\item{log}{
a logical, if TRUE, probabilities \code{p} are given as
\code{log(p)}.
}
}
\value{
All values for the \code{*ght} functions are numeric vectors:
\code{d*} returns the density,
\code{p*} returns the distribution function,
\code{q*} returns the quantile function, and
\code{r*} generates random deviates.
All values have attributes named \code{"param"} listing
the values of the distributional parameters.
}
\references{
Atkinson, A.C. (1982);
\emph{The simulation of generalized inverse Gaussian and hyperbolic
random variables},
SIAM J. Sci. Stat. Comput. 3, 502--515.
Barndorff-Nielsen O. (1977);
\emph{Exponentially decreasing distributions for the logarithm of
particle size},
Proc. Roy. Soc. Lond., A353, 401--419.
Barndorff-Nielsen O., Blaesild, P. (1983);
\emph{Hyperbolic distributions. In Encyclopedia of Statistical
Sciences},
Eds., Johnson N.L., Kotz S. and Read C.B.,
Vol. 3, pp. 700--707. New York: Wiley.
Raible S. (2000);
\emph{Levy Processes in Finance: Theory, Numerics and Empirical Facts},
PhD Thesis, University of Freiburg, Germany, 161 pages.
}
\examples{
## ght -
#
}
\keyword{distribution}