nig: Normal Inverse Gaussian Distribution

In tsdistributions: Location Scale Standardized Distributions

Normal Inverse Gaussian Distribution

Description

Density, distribution, quantile function and random number generation for the normal inverse gaussian distribution generalized parameterized in terms of mean, standard deviation, skew and shape parameters.

Usage

dnig(x, mu = 0, sigma = 1, skew = 0, shape = 1, log = FALSE)

pnig(q, mu = 0, sigma = 1, skew = 0, shape = 1, lower_tail = TRUE, log = FALSE)

qnig(p, mu = 0, sigma = 1, skew = 0, shape = 1, lower_tail = TRUE, log = FALSE)

rnig(n, mu = 0, sigma = 1, skew = 0, shape = 1)

Arguments

x, q	vector of quantiles.
mu	mean.
sigma	standard deviation.
skew	skew parameter.
shape	shape parameter.
log	(logical) if TRUE, probabilities p are given as log(p).
lower_tail	if TRUE (default), probabilities are P[X \le x] otherwise, P[X > x].
p	vector of probabilities.
n	number of observations.

Value

d gives the density, p gives the distribution function, q gives the quantile function and r generates random deviates. Output depends on x or q length, or n for the random number generator.

tsdistributions documentation built on June 8, 2025, 11:20 a.m.