arXiv 28 Feb 2026 · Statistics — Methodology
arXiv:2603.00704 · PDF · DOI · OpenAlex · Extracted main text
Two strategies are explored for robustifying classical denoising procedures for the Gaussian sequence model. First, the Hodges and Lehmann (1952) restricted Bayes approach is used to reduce sensitivity to the specification of the initial prior distribution. Second, alternatives to the Gaussian noise assumption are explored. In both cases proposals of Huber (1964) and Mallows (1978) play a crucial role.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Mallows, CL (1978) Problem 78-4, Minimizing an Integral | 1.000 | 7 | 4 | 100% |
| 2 | Huber, PJ (1964) Robust Estimation of a Location Parameter | 0.928 | 4 | 4 | 100% |
| 3 | Efron, Bradley and Morris, Carl (1971) Limiting the risk of Bayes and empirical Bayes estimators Part I: the Bayes case | 0.811 | 4 | 2 | 100% |
| 4 | Hodges, Joseph L and Lehmann, Erich L (1952) The use of previous experience in reaching statistical decisions | 0.644 | 2 | 2 | 100% |
| 5 | Kiefer, Jack and Wolfowitz, Jacob (1956) Consistency of the maximum likelihood estimator in the presence of infinitely many incidental parameters | 0.644 | 2 | 2 | 100% |
| 6 | Bickel, PJ (1983) Minimax estimation of the mean of a normal distribution subject to doing well at a point | 0.585 | 3 | 1 | 100% |
| 7 | Alfio Marazzi (1985) On constrained minimization of the Bayes risk for the linear model | 0.585 | 3 | 1 | 100% |
| 8 | Bickel, Peter J and Collins, John Richard (1983) Minimizing Fisher information over mixtures of distributions | 0.511 | 2 | 1 | 100% |
| 9 | Casella, George and Strawderman, William E (1981) Estimating a bounded normal mean | 0.511 | 2 | 1 | 100% |
| 10 | R. Koenker and I. Mizera (2014) Convex Optimization, Shape Constraints, Compound Decisions, and Empirical Bayes Rules self | 0.511 | 2 | 1 | 100% |
Showing the top 10 of 28 scored citations.