Keunwoo Lim, Ting Ye, Fang Han
arXiv 7 Feb 2025 · Mathematics — Statistics Theory
arXiv:2502.04654 · PDF · DOI · OpenAlex · Extracted main text
We propose a new minimum-distance estimator for linear random coefficient models. This estimator integrates the recently advanced sliced Wasserstein distance with the nearest neighbor methods, both of which enhance computational efficiency. We demonstrate that the proposed method is consistent in approximating the true distribution. Moreover, our formulation naturally leads to a diffusion process-based algorithm and is closely connected to treatment effect distribution estimation -- both of which are of independent interest and hold promise for broader applications.
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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 | Hoderlein, S., Klemelä, J., and Mammen, E (2010) Analyzing the random coefficient model nonparametrically | 0.874 | 5 | 2 | 100% |
| 2 | Liutkus, A., Simsekli, U., Majewski, S., Durmus, A., and Stöter, F.-R (2019) Sliced-Wasserstein flows: Nonparametric generative modeling via optimal transport and diffusions | 0.874 | 5 | 2 | 100% |
| 3 | Tanguy, E., Flamary, R., and Delon, J (2024) Properties of discrete sliced Wasserstein losses | 0.843 | 4 | 3 | 75% |
| 4 | Holzmann, H. and Meister, A (2020) Rate-optimal nonparametric estimation for random coefficient regression models | 0.811 | 4 | 2 | 100% |
| 5 | Heckman, J. J., Smith, J., and Clements, N (1997) Making the most out of programme evaluations and social experiments: Accounting for heterogeneity in programme impacts | 0.811 | 4 | 2 | 100% |
| 6 | Beran, R. and Millar, P. W (1994) Minimum distance estimation in random coefficient regression models | 0.737 | 3 | 2 | 100% |
| 7 | Dunker, F., Mendoza, E., and Reale, M (2025) Regularized maximum likelihood estimation for the random coefficients model | 0.737 | 3 | 2 | 100% |
| 8 | Gaillac, C. and Gautier, E (2022) Adaptive estimation in the linear random coefficients model when regressors have limited variation | 0.737 | 3 | 2 | 100% |
| 9 | Bonnotte, N (2013) Unidimensional and evolution methods for optimal transportation | 0.737 | 3 | 2 | 100% |
| 10 | Dunker, F., Eckle, K., Proksch, K., and Schmidt-Hieber, J (2019) Tests for qualitative features in the random coefficients model | 0.644 | 2 | 2 | 100% |
Showing the top 10 of 53 scored citations.