1\name{ghtMode}
2
3
4\alias{ghtMode}
5
6
7\title{Generalized Hyperbolic Student-t Mode}
8
9
10\description{
11
12    Computes the mode of the generalized hyperbolic
13    Student-t distribution.
14
15}
16
17
18\usage{
19ghtMode(beta = 0.1, delta = 1, mu = 0, nu = 10)
20}
21
22
23\arguments{
24
25    \item{beta, delta, mu}{
26        numeric values.
27        \code{beta} is the skewness parameter in the range \code{(0, alpha)};
28        \code{delta} is the scale parameter, must be zero or positive;
29        \code{mu} is the location parameter, by default 0.
30        These are the parameters in the first parameterization.
31        }
32    \item{nu}{
33        a numeric value, the number of degrees of freedom.
34        Note, \code{alpha} takes the limit of \code{abs(beta)},
35        and \code{lambda=-nu/2}.
36        }
37
38}
39
40
41\value{
42
43    returns the mode for the generalized hyperbolic Student-t
44    distribution. A numeric value.
45
46}
47
48
49
50\references{
51Atkinson, A.C. (1982);
52    \emph{The simulation of generalized inverse Gaussian and hyperbolic
53    random variables},
54    SIAM J. Sci. Stat. Comput. 3, 502--515.
55
56Barndorff-Nielsen O. (1977);
57    \emph{Exponentially decreasing distributions for the logarithm of
58    particle size},
59    Proc. Roy. Soc. Lond., A353, 401--419.
60
61Barndorff-Nielsen O., Blaesild, P. (1983);
62    \emph{Hyperbolic distributions. In Encyclopedia of Statistical
63    Sciences},
64    Eds., Johnson N.L., Kotz S. and Read C.B.,
65    Vol. 3, pp. 700--707. New York: Wiley.
66
67Raible S. (2000);
68    \emph{Levy Processes in Finance: Theory, Numerics and Empirical Facts},
69    PhD Thesis, University of Freiburg, Germany, 161 pages.
70}
71
72
73\examples{
74## ghtMode -
75   ghtMode()
76}
77
78
79\keyword{distribution}
80
81