Last updated: 2025-12-02

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We investigate the performance of SuSiE model for summary statistics with various types of covariance (LD) matrices. We consider 5 types of covariance matrices:

  1. In-sample LD matrix: Gold standard

  2. Out-sample LD matrix: LD matrix \(\widehat{R}\) calculated from a out-of-sample data

  3. Regularized: \(\widehat{R}_{\lambda} = (1-\lambda) * \widehat{R} + \lambda * I\) with \(\lambda = 0.1\)

  4. Truncated SVD: \(\tilde{R}\) as presented in the paper

  5. TSVD + Reg.: \(\tilde{R}_{\lambda} = (1-\lambda) * \tilde{R} + \lambda * I\) with \(\lambda = 0.1\)

Analyses: