Discussion of the Paper "Connecting Model-Based and Model-Free Approaches to Linear Least Squares Regression" by Lutz Dümbgen and Laurie Davies (2024)

Jan Hannig

doi:10.60923/issn.1973-2201/22034

Discussion of the Paper "Connecting Model-Based and Model-Free Approaches to Linear Least Squares Regression" by Lutz Dümbgen and Laurie Davies (2024)

Authors

Jan Hannig The University of North Carolina at Chapel Hill

Department of Statistics and Operations Research

DOI:

https://doi.org/10.60923/issn.1973-2201/22034

References

T. CAI, A. ZHANG (2018). Rate-optimal perturbation bounds for singular subspaces with applications to high-dimensional statistics. The Annals of Statistics, 46, no. 1, pp. 60–80.

N. CHUNG, J. STOREY (2014). Statistical significance of variables driving systematic variation in high-dimensional data. Bioinformatics, 31, no. 4, pp. 545–554.

L. DÜMBGEN, L. DAVIES (2024). Connecting model-based and model-free approaches to linear least squares regression. Statistica, 84, no. 2, pp. 65–81.

M. GAVISH, D. DONOHO (2014). The optimal hard threshold for singular values is 4/√3. IEEE Transactions on Information Theory, 60, no. 8, pp. 5040–5053.

J. PROTHERO, M. JIANG, J.HANNIG, Q. TRAN-DINH, A. ACKERMAN, J.MARRON (2024). Data integration via analysis of subspaces (divas). TEST, 33, pp. 633–674.

P.-A. WEDIN (1972). Perturbation bounds in connection with singular value decomposition. BIT Numerical Mathematics, 12, pp. 99–111.

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Published

2025-11-25

How to Cite

Hannig, J. (2024). Discussion of the Paper "Connecting Model-Based and Model-Free Approaches to Linear Least Squares Regression" by Lutz Dümbgen and Laurie Davies (2024). Statistica, 84(2), 93–95. https://doi.org/10.60923/issn.1973-2201/22034