fBasics (version 4021.93)

sght: Standardized generalized hyperbolic Student-t Distribution

Description

Density, distribution function, quantile function and random generation for the standardized generalized hyperbolic distribution.

Usage

dsght(x, beta = 0.1, delta = 1, mu = 0, nu = 10, log = FALSE)
psght(q, beta = 0.1, delta = 1, mu = 0, nu = 10)
qsght(p, beta = 0.1, delta = 1, mu = 0, nu = 10)
rsght(n, beta = 0.1, delta = 1, mu = 0, nu = 10)

Value

All values for the *sght functions are numeric vectors:

d* returns the density,

p* returns the distribution function,

q* returns the quantile function, and

r* generates random deviates.

All values have attributes named "param" listing the values of the distributional parameters.

Arguments

beta, delta, mu

numeric values. beta is the skewness parameter in the range (0, alpha); delta is the scale parameter, must be zero or positive; mu is the location parameter, by default 0. These are the parameters in the first parameterization.

nu

a numeric value, the number of degrees of freedom. Note, alpha takes the limit of abs(beta), and lambda=-nu/2.

x, q

a numeric vector of quantiles.

p

a numeric vector of probabilities.

n

number of observations.

log

a logical, if TRUE, probabilities p are given as log(p).

Author

Diethelm Wuertz.

Examples

## rsght -
   set.seed(1953)
   r = rsght(5000, beta = 0.1, delta = 1, mu = 0, nu = 10)
   plot(r, type = "l", col = "steelblue",
     main = "gh: zeta=1 rho=0.5 lambda=1")

## dsght -
   # Plot empirical density and compare with true density:
   hist(r, n = 50, probability = TRUE, border = "white", col = "steelblue")
   x = seq(-5, 5, length = 501)
   lines(x, dsght(x, beta = 0.1, delta = 1, mu = 0, nu = 10))

## psght -
   # Plot df and compare with true df:
   plot(sort(r), (1:5000/5000), main = "Probability", col = "steelblue")
   lines(x, psght(x, beta = 0.1, delta = 1, mu = 0, nu = 10))

## qsght -
   # Compute Quantiles:
   round(qsght(psght(seq(-5, 5, 1), beta = 0.1, delta = 1, mu = 0, nu =10),
               beta = 0.1, delta = 1, mu = 0, nu = 10), 4)