Talk:Generalized extreme value distribution

message: Why is the Generalized Pareto Distribution redirected to this article? First the Generalized Pareto Distribution is not the same as an Extreme Value Distriubution and second the Generalized Pareto Distribution is not mentioned a single time in the article.
:I have changed the redirect, so it points now to Pareto distribution instead. DFH 18:52, 23 December 2006 (UTC)
thread_title:  Generalized Pareto Distribution 

message: It's not completely obvious how the connection between Frechet and GEV distributions. It'll be really helpful to clean up those formulas - i.e., "mu" in the GEV distribution is not the same as "mu" in the frechet distribution. Probably similar issues with Gumbel/etc.   — Preceding unsigned comment added by 74.88.101.86 (talk) 01:18, 23 September 2014 (UTC)
thread_title:  Links to Frechet/etc 

message: I arrived at this page with a specific, practical, and probably common, problem, and did not find the solution (or else did not recognize it). The problem is, if I believe a variable x follows some distribution, then what is the formula for the expected EVD of samples of size n? It would be very helpful to provide some examples along these lines for common distributions (eg Gaussian).
My best hint is to use a statistical evaluation program, e.g. the R package "extRemes" - it can give you parameters to a fit as well as goodness-of-fit estimations.
This might be obvious, but just in case, here goes: If the pdf of x is f(x) and it's cdf is F(x) and you have N samples, the exact pdf for the maximum from a sample of size N is Nf(x)F(x)^(N-1).
[There seems to be a misconception here.  The EVD provided applies to all probability distributions asymptotically (i.e., as the number of samples increases without limit) much as the Gaussian distribution is the asymptotical limit for N summed variables of any distribution.  Obviously, different underlying distributions will have different values for the parameters. If F(x) is any cumulative distribution function, the probability that some X is the maximum of N values is given by F(X) raised to the Nth power.  Letting N increase without limit, one can derive the EVD distributions.]  —Preceding unsigned comment added by Jymcr (talk • contribs) 17:24, 4 September 2007 (UTC)
replies: text: That looks correct. 69.143.236.33 00:28, 18 October 2007 (UTC)
thread_title:  Provide practical guidance? 

message: Some References:
- To understand the three (Gumbel, Weibull and Frechet) page 7 and 8:
http://www.gloriamundi.org/picsresources/pesrgs.pdf
- An Introduction to Statistical Modeling of Extreme Values; By Stuart Coles
http://books.google.com/books?id=2nugUEaKqFEC&pg=PA1&dq=introduction+extreme+value&sig=7kZzjXGcEo7iNXDxOuUkGm_3LP0#PPA2,M1
-Extreme Values in Finance, Telecommunications, and the Environment; By Bärbel Finkenstädt, Holger Rootzén
http://books.google.com/books?hl=en&lr=&id=d55hUIBERf0C&oi=fnd&pg=PR11&dq=Generalized+Pareto+versus+Generalized+Extreme+Value&ots=mh0R8Vk1Wn&sig=TZla5IGDMRiCDJ5HLCoJVlfC4g4#PPA79,M1
Andrea Graves, 10 September 2007, London, UK.  —Preceding unsigned comment added by Andrea.graves (talk • contribs) 00:29, 10 September 2007 (UTC)
thread_title:  References with the answers you are looking for 

message: I think if xi < -1 then the formula currently stated for the mode is not correct. I think when xi <-1 the mode is at the upper limit of the distribution, mu-sigma/xi.
Also I think the formulae currently stated for the mean, variance, skewness and kurtosis are only valid if xi < 1, 1/2, 1/3 and 1/4 respectively.
Also quite a few of the formulae stated in the table need to have a separate formula given for the special case xi=0 (in the same way as is currently done for the support).Fathead99 (talk) 10:17, 3 October 2008 (UTC)
thread_title:  Some updates needed 

message: In the section Related distributions, I had to change the order of the parameters for the Weibull distribution to be consistent with the article on the Weibull distribution to which this article must surely give deference on such matters.  It gives scale parameter first, then the shape parameter.  (This is the opposite, by the way, of the convention used by R_(programming_language) in its functions rweibull, etc.)
Scwarebang (talk) 22:54, 24 November 2013 (UTC)
thread_title:  Corrected parameter order in Weibull distributions 

message: Looks like it is exp(-(x-m)/s) exp(-exp(-(x-m)/s)) to me and not exp(-(x-m)/s).
Am I wrong ?  — Preceding unsigned comment added by 87.202.21.225 (talk) 05:26, 18 December 2013 (UTC)
thread_title:  The limit "ksi = 0 

message: There was a parameter causing the problem Warning: Page using Template:Infobox probability distribution with unknown parameter "g_k" (this message is shown only in preview).
Unfortunately I do not know what that parameter means, so I am recording it below in case someone knows about it and would like to place in the article:
| g_k        = g_k=\Gamma(1-k\xi)
rendered as: g_k = g_k=\Gamma(1-k\xi)  — Preceding unsigned comment added by Walwal20 (talk • contribs) 17:05, 20 May 2020 (UTC)
thread_title:  Removal of unknown parameter from the probability distribution template 

message: For completeness, I think it would be useful to add a line to section 3.1 pointing out that the formulas of the mean, median, variance... of the minimal GEV are the same as for the maximal GEV (as one can see here: https://reference.wolfram.com/language/ref/MinStableDistribution.html)  — Preceding unsigned comment added by 2001:8A0:5745:EB01:C1B7:9C5A:3EAF:5E79 (talk) 08:40, 10 July 2021 (UTC)
thread_title:  Parameters of the minimal GEV 

message: The example of the maximum of N iiv following the normal distribution is not clear enough in its current state. What is the mentioned Φ function? The paragraph refers to the article Fisher–Tippett–Gnedenko theorem, but nothing in the latter helps understanding the claimed statement. Indeed, there is also a discussion in the latter article about the maximum of normally distributed variables, but it is quite informal and in any case, it is not clear at all how both explanations are linked.
Moreover, since no details / rigorous proofs are given, a reference would be welcome. Infisxc (talk) 13:43, 14 September 2023 (UTC)
thread_title:  Example of normal distribution unclear