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