R/dnig.R

In GeneralizedHyperbolic: The Generalized Hyperbolic Distribution

### Functions for the normal inverse Gaussian distribution

### Density of the normal inverse Gaussian distribution
dnig <- function(x, mu = 0, delta = 1, alpha = 1, beta = 0,
                    param = c(mu, delta, alpha, beta)) {

  if (length(param) != 4)
    stop("param vector must contain 4 values")

  param <- as.numeric(param)

  dghyp(x, param = c(param, -1/2))
} ## End of dnig()


### Cumulative distribution function of the
### normal inverse Gaussian distribution

pnig <- function(q, mu = 0, delta = 1, alpha = 1, beta = 0,
                 param = c(mu, delta, alpha, beta),
                 lower.tail = TRUE, subdivisions = 100,
                 intTol = .Machine$double.eps^0.25,
                 valueOnly = TRUE, ...){

  if (length(param) != 4)
    stop("param vector must contain 4 values")

  param <- as.numeric(param)

  pghyp(q, param = c(param, -1/2), lower.tail = lower.tail,
        subdivisions = subdivisions, intTol = intTol,
        valueOnly = valueOnly, ...)
} ## End of pnig()

### Quantiles function of the normal inverse Gaussian distribution
qnig <- function(p, mu = 0, delta = 1, alpha = 1, beta = 0,
                 param = c(mu, delta, alpha, beta),
                 lower.tail = TRUE, method = c("spline", "integrate"),
                 nInterpol = 501, uniTol = .Machine$double.eps^0.25,
                 subdivisions = 100, intTol = uniTol, ...) {

  if (length(param) != 4)
   stop("param vector must contain 4 values")

  param <- as.numeric(param)

  qghyp(p, param = c(param, -1/2), lower.tail = lower.tail, method = method,
        nInterpol = nInterpol, uniTol = uniTol,
        subdivisions = subdivisions, intTol = intTol, ...)
} # End of qnig()

### Function to generate random observations from a
### normal inverse Gaussian distribution using the
### mixing property of the generalized inverse
### Gaussian distribution and Dagpunar's algorithm
### for the generalized inverse Gaussian
rnig <- function(n, mu = 0, delta = 1, alpha = 1, beta = 0,
                    param = c(mu, delta, alpha, beta)) {

  if (length(param) != 4)
    stop("param vector must contain 4 values")

  param <- as.numeric(param)

  rghyp(n, param = c(param, -1/2))
} ## End of rnig()

### Derivative of the density
ddnig <- function(x, mu = 0, delta = 1, alpha = 1, beta = 0,
                  param = c(mu, delta, alpha, beta)) {

  if (length(param) != 4)
    stop("param vector must contain 4 values")

  param <- as.numeric(param)

  ddghyp(x, param = c(param, -1/2))
} ## End of ddnig()