gevcdf
Generalized extreme value (GEV) cumulative distribution function (CDF).
p = gevcdf (x, k, sigma, mu)
returns the
CDF of the generalized extreme value (GEV) distribution with shape parameter
k, scale parameter sigma, and location parameter mu,
evaluated at the values in x. The size of p is the common size
of the input arguments. A scalar input functions as a constant matrix of the
same size as the other inputs.
Default values for K, SIGMA, and MU are 0, 1, and 0, respectively.
When k < 0, the GEV is the type III extreme value distribution. When
k > 0, the GEV distribution is the type II, or Frechet, extreme value
distribution. If W has a Weibull distribution as computed by the
wblcdf
function, then -W has a type III extreme value distribution and
1/W has a type II extreme value distribution. In the limit as k
approaches 0, the GEV is the mirror image of the type I extreme value
distribution as computed by the evcdf
function.
The mean of the GEV distribution is not finite when k >= 1, and the variance is not finite when k >= 1/2. The GEV distribution has positive density only for values of x such that K*(X-MU)/SIGMA > -1.
p = gevcdf (…, "upper")
returns the upper tail probability
of the generalized extreme value distribution.
See also: gevinv, gevpdf, gevrnd, gevfit, gevlike, gevstat
Source Code: gevcdf