Ensure that the covariance matrices are positive semi-definite (PSD)#16
Open
zeyuxie29 wants to merge 1 commit intohaoheliu:mainfrom
Open
Ensure that the covariance matrices are positive semi-definite (PSD)#16zeyuxie29 wants to merge 1 commit intohaoheliu:mainfrom
zeyuxie29 wants to merge 1 commit intohaoheliu:mainfrom
Conversation
…errors in the calculation of imaginary components.
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
2 participants
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
Ensure that the covariance matrices are positive semi-definite (PSD) to prevent errors in the calculation of imaginary components arising from negative eigenvalues.
Reason for Imaginary Components
Covariance matrices are theoretically positive semi-definite (PSD). However, due to floating-point arithmetic errors, their estimated values may become near-psd with tiny negative eigenvalues. When computing covmean (e.g., via operations like sqrtm()), this numerical instability can lead to non-real (complex) results, causing runtime errors in the code.
Summary of Changes:
Check Positivity: Calculate eigenvalues of covariance matrices and identify if either matrix has a negative minimum eigenvalue.
Regularize Non-Positive-Definite Matrices: For matrices with negative minima, add eps * I to enforce strict positive definiteness.