Talk:Copula (statistics)

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The lead is probably confusing in practice, though technically correct. The main reason to use a copula is to produce a joint distribution with specified marginals. The lead gives almost the opposite impression.

[edit] Wrong Figure ?

The fig "Gaussian_Copula_PDF.png" is maybe wrong: Since C(u,v): [0,1]×[0,1]→[0,1] the surface cannot rise over 1. However, as you see on the figure, the surface goes almost up to 3 ...

Panhypersebastos 08:13, 1 June 2007 (UTC)Panhypersebastos

It is okay. The depicted graph is a density of a copula (as mentioned below the picture), not a copula itself. --PeterSarkoci 10:12, 31 July 2007 (UTC)
I changed it, so that we have a comparison between cumulative and density. I hope it is more clear since the previous one caused misunderstandings. --Matteo Zandi

I like the Figures, but is there any chance of adding some alternative views for the existing cases, so as to make things easier to interpret? Melcombe (talk) 13:31, 19 March 2008 (UTC)

[edit] This article needs a complete rewrite :-(

I came to this article from the Correlation article, which states:

The information given by a correlation coefficient is not enough to define the dependence structure between random variables; to fully capture it we must consider a copula between them.

Unfortunately the copula article doesn't help at all with this. The first paragraph is almost unintelligible, as is becoming more and more frequent in Wikipedia. This is supposed to be an encyclopedia -- the vast majority of people looking something up are not specialists in the subject, and the articles should be aimed at them. Starting with "a multivariate joint distribution defined on the n-dimensional unit cube" followed by a bunch of mathematics effectively says "Go away; this page is not for the likes of you!".

The assertion on this talk page that a copula is useful for generating a joint distribution from a specified set of marginals is intriguing. (In fact it's pretty well what I want to do.) Please can someone who knows how to do it show us how it's done, preferably with a simple numerical example we can work through. The simpler the better please; we're not all left-brained mathematical geniuses (unlike the folk who seem to generate such articles). Nevertheless, reasonably intelligent people can often understand things if they're explained in simple terms. We may be ignorant, but we're not stupid.

Put the main ideas first, and leave the gory details until near the end of the article.

I'll now have to resort to Google to find out what a copula is.

--84.9.73.5 (talk) 11:12, 23 December 2007 (UTC)

Update: This article gives a much gentler introduction.

--84.9.73.5 (talk) 14:56, 23 December 2007 (UTC)

[edit] Notations for Cartesian products

This appears in the article:

$B=\times_{i=1}^{n}[x_i,y_i]\subseteq [0,1]^n;$

I'm wondering if there are particular views on advantages and disadvantages of this particular notation for Cartesian products, as contrasted with this:

$B=\prod_{i=1}^{n}[x_i,y_i]\subseteq [0,1]^n;$