1. Tyler, David E. and Mengxi Yi. "Lassoing Eigenvalues." Biometrika. 2020, Vol. 107, No. 2, 397–414.

  2. Yi, Mengxi and David E. Tyler. "Shrinking the sample covariance matrix using convex penalties on the matrix-log transformation." Journal of Computational and Graphical Statistics. 2021, Vol. 30, No. 2, 442-451.

  3. Muhlmann, Christoph, Klaus Nordhausen and Mengxi Yi. "Multivariate spatial prediction in a blind source separation framework." IEEE Geoscience and Remote Sensing Letters. 2021, Vol. 18, No. 11, 1931-1935.

Working Papers

  1. Muhlmann, Christoph, François Bachoc, Klaus Nordhausen and Mengxi Yi. "Test of the Latent Dimension of a Spatial Blind Source Separation Model." Submitted.

  2. Tyler, David E. and Mengxi Yi. "Breakdown points of penalized and hybrid M-estimators of covariance." To be submitted.

Selected Grants

  • NSFC Grant, Robust Estimation of Covariance Matrices under Geodesic Convex Penalty Functions, 2022-2024, CNY 300,000, PI.

  • Austrian Science Fundation (FWF) P-31881, Blind Source Separation in Time and Space, 2019-2022, €399,984.39, Co-PI.

  • USA NSF Grants, DMS-1812198,Lassoing Eigenvalues: A classical and a robust approach,2018-2021, $149,997, Co-PI.

Professional Services

  • Reviewer for Annals of Statistics, Annals of Applied Probability, Statistica Sinica, Journal of Multivariate Analysis.

  • Statistical Consultant, Rutgers Office of Statistical Consulting