On least squares estimation under heteroscedastic and heavy-tailed errors
Author:
Affiliation:
1. Department of Statistics and Data Science, Carnegie Mellon University
2. Department of Statistics, University of Florida
Publisher
Institute of Mathematical Statistics
Subject
Statistics, Probability and Uncertainty,Statistics and Probability
Reference74 articles.
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2. Audibert, J.-Y. and Catoni, O. (2011). Robust linear least squares regression. Ann. Statist. 39 2766–2794.
3. Birgé, L. and Massart, P. (1998). Minimum contrast estimators on sieves: exponential bounds and rates of convergence. Bernoulli 4 329–375.
4. Chatterjee, S. and Lafferty, J. (2019). Adaptive risk bounds in unimodal regression. Bernoulli 25 1–25.
5. Ghosal, P. and Sen, B. (2017). On univariate convex regression. Sankhya A 79 215–253.
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1. Local convergence rates of the nonparametric least squares estimator with applications to transfer learning;Bernoulli;2024-08-01
2. Least squares estimation of a quasiconvex regression function;Journal of the Royal Statistical Society Series B: Statistical Methodology;2023-12-12
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