evinv
Inverse of the extreme value cumulative distribution function (iCDF).
For each element of p, compute the inverse cdf for a type 1 extreme value distribution with location parameter mu and scale parameter sigma. The size of x is the common size of p, mu and sigma. A scalar input functions as a constant matrix of the same size as the other inputs.
Default values are mu = 0, sigma = 1.
When called with three output arguments, [x, xlo,
xup]
it computes the confidence bounds for x when the input
parameters mu and sigma are estimates. In such case, pcov,
a 2-by-2 matrix containing the covariance matrix of the estimated parameters,
is necessary. Optionally, alpha has a default value of 0.05, and
specifies 100 * (1 - alpha)% confidence bounds. xlo and xup
are arrays of the same size as x containing the lower and upper
confidence bounds.
The type 1 extreme value distribution is also known as the Gumbel
distribution. The version used here is suitable for modeling minima; the
mirror image of this distribution can be used to model maxima by negating
x. If y has a Weibull distribution, then
x = log (y)
has the type 1 extreme value distribution.
See also: evcdf, evpdf, evrnd, evfit, evlike, evstat
Source Code: evinv