Research Interests

  • Analysis of non-Euclidean and tensor data

  • Algebraic statistics and graphical models

  • Information geometry

  • Decision theory

    My work currently focuses on problems at the intersection of algebra, geometry and statistics. One particular area I am interested in is the statistical analysis of non-Euclidean data. Classical statistical techniques can usually only be partially leveraged to deal with non-Euclidean data, presenting distinct challenges. A second, related topic that I like to think about is the study of the geometry and symmetries of statistical models. If you are interested in these areas please do not hesitate to reach out!


  • Drton, M., Grosdos A., McCormack A. (2024). Rational Maximum Likelihood Estimators of Kronecker Covariance Matrices. arXiv preprint
    arXiv:2401.08280. arXiv

  • McCormack A., Hoff, P. (2023). Information Geometry and Asymptotics for Kronecker Covariances. arXiv preprint arXiv:2308.02260.


  • McCormack, A. & Hoff, P. (2023). Equivariant Estimation of Fréchet Means. (Accepted, Biometrika)

  • McCormack, A. & Hoff, P. (2022). The Stein Effect for Fréchet Means. Ann. Statist, 50 (6), 3647 - 3676.
    arXiv  AOS  PDF

  • McCormack, A. & Hoff, P. (2022). Tests of Linear Hypotheses using Indirect Information. (Accepted, Canadian Journal of Statistics)

  • Hoff, P., McCormack A. & Zhang, A. R. (2022). Core Shrinkage Covariance Estimation for Matrix-variate Data. (Accepted, JRSS B).

  • McCormack, A., Reid, N., Sartori, N., & Theivendran, S. A. (2019). A directional look at F tests. Canadian Journal of Statistics, 47(4), 619-627.
    arXiv  CJS