Specific Generalized Inverse Gaussian Moments and Mode {HyperbolicDist} | R Documentation |
Moments and Mode of the Generalized Inverse Gaussian Distribution
Description
Functions to calculate the mean, variance, skewness, kurtosis and mode of a specific generalized inverse Gaussian distribution.
Usage
gigMean(Theta)
gigVar(Theta)
gigSkew(Theta)
gigKurt(Theta)
gigMode(Theta)
Arguments
Theta |
Parameter vector of the generalized inverse Gaussian distribution. |
Value
gigMean
gives the mean of the generalized inverse Gaussian
distribution, gigVar
the variance, gigSkew
the skewness,
gigKurt
the kurtosis, and gigMode
the mode. The formulae
used are as given in Jorgensen (1982),
pp. 13–17. Note that the kurtosis is the standardised fourth cumulant
or what is sometimes called the kurtosis excess. (See
http://mathworld.wolfram.com/Kurtosis.html for a discussion.)
The parameterization used for the generalized inverse Gaussian
distribution is the (\chi,\psi)
one (see
dgig
). To use another parameterization, use
gigChangePars
.
Author(s)
David Scott d.scott@auckland.ac.nz
References
Jorgensen, B. (1982). Statistical Properties of the Generalized Inverse Gaussian Distribution. Lecture Notes in Statistics, Vol. 9, Springer-Verlag, New York.
See Also
Examples
Theta <- c(-0.5,5,2.5)
gigMean(Theta)
gigVar(Theta)
gigSkew(Theta)
gigKurt(Theta)
gigMode(Theta)