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Something appears to be missing in the statement of the theorem:
First, it seems that the terms on the right of the equation should be expressed as Ut Q_i U, with Q_i being a matrix and U being the vector of normals. This way the statement that Q_i is of rank r_i has some meaning - r.v.'s don't have a rank.
Second, for the theorem to hold, there must be some constraint on the relationship between the Q's, otherwise they could, for example, be identical, and they would definitely not be independent.
--184.108.40.206 16:49, 24 Jun 2005 (UTC)
Who is Cochran?
There are no references included in the article. Cochran's theorem appears in many textbooks, but statements made in the Example — albeit appropriately derived — are new to me. I'm particularly interested in — does it appear in a book or is it the editor's own contribution? Ml78712 08:11, 28 June 2007 (UTC)
- There needs to be a reference to where Cochran first published his theorem. I am not a dog (talk) 15:39, 18 April 2008 (UTC)
- The whole article needs to be rewritten. Whoever wrote the article was likely taking as the maximum likelihood estimator of , which does use a denominator of n. But that ought to be stated clearly.
- The whole theorem is really better stated as a theorem regarding quadratic forms of Normal random variables. In that case, if , then if and only if and and for every . That is, the matrices that define the quadratic forms must idempotent and orthogonal. Moreover, where is the rank of
- The original citation is Cochran, W.G., "The Distribution of Quadratic Forms in a Normal System", Proc. Cam. Phil. Soc. (1934), 178. (That citation was pulled from Greybill's Matrices with applications in Statistics.)
Rank of Qi needs expaining
In Overview, more careful definition and explanation is needed. What is a rank of sum of squares of linear combinations? Are they supposed to be thought of as symmetric bilinear forms? Xenonice (talk) 02:19, 2 October 2008 (UTC)
- Definitely they are supposed to be thought of as symmetric bilinear forms. More later........ Michael Hardy (talk) 02:30, 2 October 2008 (UTC)
Expert subject tag
I have added the expert-subject tag for statistics as there has been no action relating to the general "factual acccuracy" tag, which presumably relates to the discussion above. Melcombe (talk) 16:36, 26 May 2010 (UTC)
The sign ~ in "alternative formulation"
I presume that the sign ~ in the following extract from the article was not supposed to be an unreadable superscript. If there were no explanation added in the verbal form, the formula would need more guessing to understand, yet I believe it still deserves a small correction. M-
The following version is often seen when considering linear regression.
Suppose is a standard multivariate Gaussian random variable