Gumbeldf
Jump to navigation
Jump to search
Purpose
Gumbel distribution.
Synopsis
- prob = gumbeldf(function,x,a,b)
Description
Estimates cumulative distribution function (cumulative, cdf), probability density function (density, pdf), quantile (inverse of cdf), or random numbers for a Gumbel distribution.
This distribution is also known as the Type I extreme value distribution. It is an alternative to the Weibull distribution.
Inputs
- function = [ {'cumulative'} | 'density' | 'quantile' | 'random' ], defines the functionality to be used. Note that the function recognizes the first letter of each string so that the string could be: [ 'c' | 'd' | 'q' | 'r' ].
- x = matrix in which the sample data is stored, in the interval (-inf,inf).
- for function=quantile - matrix with values in the interval (0,1).
- for function=random - vector indicating the size of the random matrix to create.
- a = mode/location parameter (real).
- b = scale parameter (real and positive).
Note: If inputs (x, a, and b) are not equal in size, the function will attempt to resize all inputs to the largest input using the RESIZE function.
Note: Functions will typically allow input values outside of the acceptable range to be passed but such values will return NaN in the results.
Examples
Cumulative
>> prob = gumbeldf('c',0.99,0.5,1) prob = 0.5419 >> x = [0:0.1:10]; >> plot(x,gumbeldf('c',x,2),'b-',x,gumbeldf('c',x,0.5),'r-')
Density
>> prob = gumbeldf('d',0.99,0.5,1) prob = 0.3320 >> x = [0:0.1:10]; >> plot(x,gumbeldf('d',x,2),'b-',x,gumbeldf('d',x,0.5),'r-')
Quantile
>> prob = gumbeldf('q',0.99,0.5,1) prob = 5.1001
Random
>> prob = gumbeldf('r',[4 1],2,1) ans = 3.8437 2.6508 2.3566 4.2479
See Also
betadf, cauchydf, chidf, expdf, gammadf, laplacedf, logisdf, lognormdf, normdf, paretodf, raydf, triangledf, unifdf, weibulldf