R: Standardized Generalized Hyperbolic Distribution

sgh {fBasics} | R Documentation

## Standardized Generalized Hyperbolic Distribution

### Description

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

### Usage

    dsgh(x, zeta = 1, rho = 0, lambda = 1, log = FALSE)
    psgh(q, zeta = 1, rho = 0, lambda = 1)
    qsgh(p, zeta = 1, rho = 0, lambda = 1)
    rsgh(n, zeta = 1, rho = 0, lambda = 1)

### Arguments

`zeta, rho, lambda` | shape parameter `zeta` is positive, skewness parameter `rho` is in the range (-1, 1).
`log` | a logical flag by default `FALSE`. If TRUE, log values are returned.
`n` | number of observations.
`p` | a numeric vector of probabilities.
`x, q` | a numeric vector of quantiles.

### Details

The generator `rsgh` is based on the GH algorithm given by Scott (2004).

### Value

All values for the `*sgh` 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.

### Author(s)

Diethelm Wuertz.

### Examples

    ## rsgh -
       set.seed(1953)
       r = rsgh(5000, zeta = 1, rho = 0.5, lambda = 1)
       plot(r, type = "l", col = "steelblue",
         main = "gh: zeta=1 rho=0.5 lambda=1")

    ## dsgh -
       # Plot empirical density and compare with true density:
       hist(r, n = 50, probability = TRUE, border = "white", col = "steelblue",
         ylim = c(0, 0.6))
       x = seq(-5, 5, length = 501)
       lines(x, dsgh(x, zeta = 1, rho = 0.5, lambda = 1))

    ## psgh -
       # Plot df and compare with true df:
       plot(sort(r), (1:5000/5000), main = "Probability", col = "steelblue")
       lines(x, psgh(x, zeta = 1, rho = 0.5, lambda = 1))

    ## qsgh -
       # Compute Quantiles:
       round(qsgh(psgh(seq(-5, 5, 1), zeta = 1, rho = 0.5), zeta = 1, rho = 0.5), 4)

[Package fBasics version 3042.89 Index]