Function Reference: evinv

statistics: x = evinv (p)
statistics: x = evcdf (p, mu)
statistics: x = evinv (p, mu, sigma)
statistics: [x, xlo, xup] = evinv (p, mu, sigma, pcov)
statistics: [x, xlo, xup] = evinv (p, mu, sigma, pcov, alpha)

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