Proving a linear algebra equation

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Discussion Overview

The discussion revolves around proving the equivalence of two multivariate formulas in the context of linear algebra, specifically within Bayesian statistics. Participants are exploring the mathematical relationships and assumptions underlying the formulas, as well as their implementation in MATLAB.

Discussion Character

  • Technical explanation
  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • One participant expresses difficulty in proving the equivalence of two formulas, A and B, and provides specific mathematical expressions and assumptions.
  • Another participant clarifies that "Sigma" (Σ) refers to a matrix rather than a summation symbol, indicating a potential misunderstanding of notation.
  • A subsequent reply confirms the clarification about Σ and elaborates that the problem is situated within Bayesian statistics, where the variables represent observations and factors, and all Σ symbols denote variance-covariance matrices.

Areas of Agreement / Disagreement

There is no consensus on the proof itself, as the initial participant seeks assistance while others clarify notation and context. The discussion remains unresolved regarding the proof of equivalence.

Contextual Notes

Participants mention specific assumptions regarding the invertibility of matrices and the relationship between the number of observations (N) and factors (F), which may affect the proof's validity.

IlyaMath
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I am having trouble proving that two multivariate formulas are equivalent. I implemented them in MATLAB and numerically they appear to be equivalent.

I would appreciate any help on this.

Prove A = B


A = (Σπ^-1 + Σy^-1)^-1 * (Σπ^-1*π + Σy^-1*y)

y = π+ X*β

Σπ =τ*Σ

Σy = X' * Σβ * X + ΣεB = (Σπ^-1 + P'*Σβ^-1*P)^-1 * (Σπ^-1*π + P'*Σβ^-1*q)

q = P*y

P = (X'*Σ^-1*X)^-1*X'*Σ^-1Assumptions

i) Σε is infinitesimally small. (If Σε is exactly zero, then Σy may not be invertible).

ii) N > F (If N = F, then the proof is trivial. If N < F then is probably not invertible and P is not defined.)Notation

A, B: Nx1

π: Nx1

y: Nx1

q: Fx1

β: Fx1

Σ: NxN

Σπ: NxN

Σy: NxN

Σβ: FxF

Σε: NxN

X: NxF

P: FxN

τ: 1x1
 

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"Sigma", [itex]\Sigma[/itex], here, is a matrix, not a summation symbol?
 
Yes, HallsofIvy, you are correct...
 
This problem comes from Bayesian statistics, where N is number of observations and F is number of factors. All of the Sigma (Σ) are variance-covariance matrices. The Greek characters after each Σ are meant to be subscripts.
 

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