Talk:Quadratic form (statistics)
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{\displaystyle \operatorname {cov} \left[\epsilon ^{T}\Lambda _{1}\epsilon ,\epsilon ^{T}\Lambda _{2}\epsilon \right]=2\operatorname {tr} \left[\Lambda _{1}\Sigma \Lambda _{2}\Sigma \right]+4\mu ^{T}\Lambda _{1}\Sigma \Lambda _{2}\mu }
If {\displaystyle \Lambda _{1}^{T}=\Lambda _{2}} and they are not symmetric, the above formula contradicts the variance formula, since in that case {\displaystyle \epsilon ^{T}\Lambda _{1}\epsilon =\epsilon ^{T}\Lambda _{2}\epsilon }. How to resolve this? Btyner 04:48, 3 April 2006 (UTC) [reply ]
- Yikes, the expression was wrong in the case of nonsymmetric {\displaystyle \Lambda }s. I have noted the symmetric requirement, and added a section showing how to derive the general expression. Btyner 18:24, 6 April 2006 (UTC) [reply ]
Is symmetry really necessary for the expectation result?
[edit ]Nothing in the usual proof of the result for expectation seems to require symmetry of {\displaystyle \Lambda }:
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{\displaystyle \operatorname {E} (\epsilon ^{T}\Lambda \epsilon )} = {\displaystyle \operatorname {E} [\operatorname {tr} (\epsilon ^{T}\Lambda \epsilon )]}= {\displaystyle \operatorname {E} [\operatorname {tr} (\Lambda \epsilon \epsilon ^{T})]}= {\displaystyle \operatorname {tr} (\Lambda \operatorname {E} [\epsilon \epsilon ^{T}])}= {\displaystyle \operatorname {tr} (\Lambda [\mu \mu ^{T}+\Sigma ])}= {\displaystyle \mu ^{T}\Lambda \mu +\operatorname {tr} (\Lambda \Sigma )}
Geomon 23:30, 21 December 2006 (UTC) [reply ]
- Good call. I must have been thinking about bilinear forms when I wrote that. Btyner 00:16, 23 January 2007 (UTC) [reply ]