Inverse Gaussian distribution
invgauss.Rd
Density, distribution function, and random generation for the inverse Gaussian distribution.
Usage
dinvgauss(x, mean = 1, shape = 1, log = FALSE)
pinvgauss(q, mean = 1, shape = 1, lower.tail = TRUE, log.p = FALSE)
qinvgauss(p, mean = 1, shape = 1, lower.tail = TRUE, log.p = FALSE, ...)
rinvgauss(n, mean = 1, shape = 1)
Arguments
- x, q
vector of quantiles, must be positive.
- mean
location parameter
- shape
shape parameter, must be positive.
- log, log.p
logical; if
TRUE
, probabilities/ densities \(p\) are returned as \(\log(p)\).- lower.tail
logical; if
TRUE
, probabilities are \(P[X <= x]\), otherwise, \(P[X > x]\).- p
vector of probabilities
- ...
additional parameter passed to
statmod::qinvgauss
for numerical evaluation of the quantile function.- n
number of random values to return
Value
dinvgauss
gives the density, pinvgauss
gives the distribution function, qinvgauss
gives the quantile function, and rinvgauss
generates random deviates.