Weighted Covariance: Calculating 3x3 Matrix with Point Weights

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To calculate a weighted covariance matrix for a 3x3 matrix of (x,y,z) coordinates, it is essential to incorporate the weighting values into the covariance formula. The standard covariance calculation does not account for weights, which can skew results if not adjusted. The discussion references a Wikipedia link that outlines the weighted covariance formula, but there is a request for clarification on its derivation. Understanding how to integrate weights into the covariance calculation is crucial for accurate analysis of the data set. Further assistance in breaking down the equation is sought to enhance comprehension.
preet
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Hi All,

I have a data set consisting of (x,y,z) coordinates. I can calculate the covariance between them just fine. Calculating all the covariances between the three variables gives me a nice 3x3 matrix. However, the points have a weighting value as well. I don't know how to account for the point weights in the normal covariance formula.

I would appreciate any advice.


Regards,

-Preet
 
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Thank you. I had seen that link... I don't understand how the equation in the provided link was derived. I we hoping someone could help flesh it out.
 
I was reading a Bachelor thesis on Peano Arithmetic (PA). PA has the following axioms (not including the induction schema): $$\begin{align} & (A1) ~~~~ \forall x \neg (x + 1 = 0) \nonumber \\ & (A2) ~~~~ \forall xy (x + 1 =y + 1 \to x = y) \nonumber \\ & (A3) ~~~~ \forall x (x + 0 = x) \nonumber \\ & (A4) ~~~~ \forall xy (x + (y +1) = (x + y ) + 1) \nonumber \\ & (A5) ~~~~ \forall x (x \cdot 0 = 0) \nonumber \\ & (A6) ~~~~ \forall xy (x \cdot (y + 1) = (x \cdot y) + x) \nonumber...

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