English

COBRA: A Combined Regression Strategy

Statistics Theory 2019-05-24 v4 Methodology Statistics Theory

Abstract

A new method for combining several initial estimators of the regression function is introduced. Instead of building a linear or convex optimized combination over a collection of basic estimators r1,,rMr_1,\dots,r_M, we use them as a collective indicator of the proximity between the training data and a test observation. This local distance approach is model-free and very fast. More specifically, the resulting nonparametric/nonlinear combined estimator is shown to perform asymptotically at least as well in the L2L^2 sense as the best combination of the basic estimators in the collective. A companion R package called \cobra (standing for COmBined Regression Alternative) is presented (downloadable on \url{http://cran.r-project.org/web/packages/COBRA/index.html}). Substantial numerical evidence is provided on both synthetic and real data sets to assess the excellent performance and velocity of our method in a large variety of prediction problems.

Keywords

Cite

@article{arxiv.1303.2236,
  title  = {COBRA: A Combined Regression Strategy},
  author = {Gérard Biau and Aurélie Fischer and Benjamin Guedj and James Malley},
  journal= {arXiv preprint arXiv:1303.2236},
  year   = {2019}
}

Comments

42 pages

R2 v1 2026-06-21T23:39:21.477Z