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

Christian Martin Hennig

doi:10.60923/issn.1973-2201/22200

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

Authors

Christian Martin Hennig University of Bologna, ALMA MATER STUDIORUM, Italy

Department of Statistical Sciences "Paolo Fortunati"

DOI:

https://doi.org/10.60923/issn.1973-2201/22200

References

P. L. DAVIES (2014). Data Analysis and Approximate Models. Chapman and Hall/CRC, New York.

P. L. DAVIES (2024). An approximation based theory of linear regression. URL https://arxiv.org/abs/2402.09858.

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

C. HENNIG (2023). Probability models in statistical data analysis: Uses, interpretations, frequentism-as-model. In B. SRIRAMAN (ed.), Handbook of the History and Philosophy of Mathematical Practice, Springer, Cham, pp. 1411–1458. URL https://arxiv.org/abs/2007.05748.

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Published

2025-11-25

How to Cite

Hennig, C. M. (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), 101–103. https://doi.org/10.60923/issn.1973-2201/22200