Semi-Positive Definiteness of Product of Symmetric Matrices

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SUMMARY

The discussion focuses on the semi-positive definiteness of the product of symmetric matrices, specifically addressing the conditions under which the element-wise product of a projection matrix P and a symmetric matrix A results in a positive semidefinite (psd) matrix. The projection matrix P is defined as P = X*inv(X'*X)*X', where X is a regressor matrix in a least squares problem. The user has conducted numerical experiments using MATLAB, concluding that the matrix (P.*A)*P is psd, while P*(P.*A)*(I-P) has all zero eigenvalues, indicating indeterminacy. The user seeks to establish formal proofs for these results and inquire about theorems related to the center submatrix of matrix A.

PREREQUISITES
  • Understanding of projection matrices, specifically symmetric and idempotent properties.
  • Familiarity with the Hadamard product and its implications for matrix operations.
  • Knowledge of positive semidefinite (psd) matrices and eigenvalue analysis.
  • Proficiency in MATLAB for numerical experimentation and matrix manipulation.
NEXT STEPS
  • Research theorems related to the properties of center submatrices in symmetric matrices.
  • Explore conditions under which the product of two symmetric matrices is positive semidefinite.
  • Learn about the implications of commuting matrices on their product's definiteness.
  • Investigate MATLAB functions for eigenvalue computation and matrix definiteness testing.
USEFUL FOR

This discussion is beneficial for mathematicians, data scientists, and engineers working with linear algebra, particularly those involved in optimization problems and matrix theory. It is especially relevant for individuals utilizing MATLAB for numerical analysis of matrix properties.

iamhappy
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Here is my problem. Any ideas are appreciated.

Let P be a projection matrix (symmetric, idempotent, positive semidefinite with 0 or 1 eigenvalues). For example, P = X*inv(X'*X)*X' where X is a regressor matrix in a least square problem.

Let A be a symmetric real matrix with only integer elements where the center submatrix (of a given size) is a (square, of course) matrix with identical elements, say 5. But the other elements of A are all smaller than the (common) element of the center submatrix (say, 5).

Q1: Is (P.*A)*P psd, nsd or indeterminant? where P.*A is the element-wise product of P and A (the Hadamard product)

Q2: Is P*(P.*A)*(I-P) psd, nsd or indeterminant? where I is the identity matrix of conformable size.

Comments: I have done some numerical examples in Matlab and it seems that the first matrix is psd and the second matrix has all zero eigenvalues (but not a zero matrix). Any idea as to how to prove the results?
 
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I think I can show Q2 now. Q1 is still a puzzle. Any help is appreciated.
Also regarding the matrix A, does anyone know of a theorem regarding the center submatrix of a matrix?
 


To put this simply, we know in general that if A and B are psd their product A*B is NOT necessarily psd.

Does anyone know when the product is indeed psd? I am looking for conditions on A and B to ensure the psd of their product.

Thanks a bunch
 


AB is not even necessarily symmetric. Consider the case where A and B commute (simple case A,B diagonal).
 

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