Misplaced Pages

Gumbel distribution: Difference between revisions

Article snapshot taken from Wikipedia with creative commons attribution-sharealike license. Give it a read and then ask your questions in the chat. We can research this topic together.
Browse history interactivelyNext edit →Content deleted Content addedVisualWikitext
Revision as of 21:00, 17 July 2003 editRselsick (talk | contribs)3 editsNo edit summary  Revision as of 21:42, 17 July 2003 edit undoJiang (talk | contribs)43,437 editsmNo edit summaryNext edit →
Line 1: Line 1:
The '''Gumbel Distribution''' is used to find the minimum (or the maximum) of a number of samples of various distributions.These distributions could be of the normal or exponential type.It is used for the extreme values of water
THE GUMBEL DISTRIBUTION

The Gumbel Distribution is used to find the minimum (or the maximum) of a number of samples of various distributions.These distributions could be of the
normal or exponential type.It is used for the extreme values of water
levels , floods and wind velocities. levels , floods and wind velocities.


It is sometimes called the Fisher-Tippet Distribution and is defined as ; It is sometimes called the Fisher-Tippet Distribution and is defined as ;
p=exp(-exp((A-x)/B) p=exp(-exp((A-x)/B)




A more practicle way of using the distribution could be A more practicle way of using the distribution could be
Line 28: Line 21:


Q3=A-B*ln(-ln(.75)) Q3=A-B*ln(-ln(.75))





The mean is A+g*B 'g=Eulers constant = .57721 The mean is A+g*B 'g=Eulers constant = .57721

Revision as of 21:42, 17 July 2003

The Gumbel Distribution is used to find the minimum (or the maximum) of a number of samples of various distributions.These distributions could be of the normal or exponential type.It is used for the extreme values of water levels , floods and wind velocities.

It is sometimes called the Fisher-Tippet Distribution and is defined as ;

      p=exp(-exp((A-x)/B)

A more practicle way of using the distribution could be

     p=exp(-exp(-0.367*(A-x)/(A-M))  ;-.367=ln(-ln(.5))

where M is the Median.To fit values one could get the Median straight away and then vary A untill it fits the list of values.

Its variates(ie to get a list of random values) can be given as ;

      x=A-B*ln(-ln(rnd))

Its percentiles can be given by ;

      x=A-B*ln(-ln(p))

ie Q1=A-B*ln(-ln(.25))

The Median is A-B*ln(-ln(.5))

 Q3=A-B*ln(-ln(.75))

The mean is A+g*B 'g=Eulers constant = .57721

The sd = B * Pi()* sqr(1/6)

Its mode is A