Inv.gaussian {VGAM} | R Documentation |
The Inverse Gaussian Distribution
Description
Density, distribution function and random generation for the inverse Gaussian distribution.
Usage
dinv.gaussian(x, mu, lambda, log = FALSE)
pinv.gaussian(q, mu, lambda)
rinv.gaussian(n, mu, lambda)
Arguments
x , q |
vector of quantiles. |
n |
number of observations.
If |
mu |
the mean parameter. |
lambda |
the |
log |
Logical.
If |
Details
See inv.gaussianff
, the VGAM family function
for estimating both parameters by maximum likelihood estimation,
for the formula of the probability density function.
Value
dinv.gaussian
gives the density,
pinv.gaussian
gives the distribution function, and
rinv.gaussian
generates random deviates.
Note
Currently qinv.gaussian
is unavailable.
Author(s)
T. W. Yee
References
Johnson, N. L. and Kotz, S. and Balakrishnan, N. (1994). Continuous Univariate Distributions, 2nd edition, Volume 1, New York: Wiley.
Taraldsen, G. and Lindqvist, B. H. (2005). The multiple roots simulation algorithm, the inverse Gaussian distribution, and the sufficient conditional Monte Carlo method. Preprint Statistics No. 4/2005, Norwegian University of Science and Technology, Trondheim, Norway.
See Also
Examples
## Not run: x <- seq(-0.05, 4, len = 300)
plot(x, dinv.gaussian(x, mu = 1, lambda = 1), type = "l",
col = "blue",las = 1, main =
"blue is density, orange is cumulative distribution function")
abline(h = 0, col = "gray", lty = 2)
lines(x, pinv.gaussian(x, mu = 1, lambda = 1), type = "l", col = "orange")
## End(Not run)