Inverse-Gaussian Distribution

Density and random generation for an Inverse-Gaussian (Wald) distribution.

Usage

density_inverse_gaussian(shape, scale, x)

random_inverse_gaussian(shape, scale, n)

Arguments

shape, scale

shape and scale parameters.

x

vector of quantiles.

n

number of observations.

Value

numeric vector

Functions density_XXX and cdf_XXX return numeric vectors of same length as x. Function random_XXX returns a numeric vector of length n).

Examples

# Probability density function for an Inverse Gaussian distribution
z <-density_inverse_gaussian(shape = 1, scale = 2, x = 0.1* 0:30)
# Generating a random vector with each component drawn from an Inverse Gaussian distribution
# with shape 1 and scale 2
z<-random_inverse_gaussian(shape = 1, scale = 2, n = 5)
z
#> [1] 1.0258558 1.8230529 0.6431899 1.1934082 0.3395203