Model selection for regression on a fixed design

By Y. Baraud. 2000

139 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/4182b22ff2d3d3585b8667e622cc4103091c99ec

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In Control and Systems Engineering

In Statistics and Probability

Citations in the corpus

Theory of classification : a survey of some recent advances (2005, methodology): “use of sharp concentration inequalities in solving model selection problems, see also Baraud [19], Castellan [56] for illustrations in regression and density estimation.”
Consistent covariate selection and post model selection inference in semiparametric regression (2004, methodology): “1, page 478, in Baraud (2000) to bound the first term in either (3.12) or (3.13). We discuss first (3.12). Notice that E‖PKnW‖(2)n = σ2 tr(PKn)/n = σ(2)rKn/n, using the standard properties of the projection operator. Then, by Corollary 5.1 of Baraud (2000), for any p≥ 2 such that E|W1| <∞ and for an”
ADAPTIVE ESTIMATION OF A QUADRATIC FUNCTIONAL BY MODEL SELECTION (2001, methodology): “This method has been successfully developed to estimate adaptively a function s in various contexts [see Birgé and Massart (1997), Barron, Birgé and Massart (1999), Baraud (1997) or Birge and Massart (2000b)].”
Model selection for regression on a random design (2002, methodology): “1 in Baraud [1] Eξ [‖s− s̃‖2n] ≤ R(2) n = C [ inf m∈Mn ( inf t∈Sm ‖s− t‖(2)n + pen(m) ) + Σn n ] ,”
ADAPTIVE TESTS OF LINEAR HYPOTHESES BY MODEL SELECTION (2003, methodology): “We refer, for example, to the work of Birgé and Massart (2001) in the context of Gaussian errors and to Baraud (2000a) under weaker assumptions.”
Adaptive estimation of the intensity of inhomogeneous Poisson processes via concentration inequalities (2003, methodology): “Baraud used it too in the regression framework (see [3]).”
Adaptive estimation of mean and volatility functions in (auto-)regressive models (2002, methodology): “Since the random variables Xi are geometrically β-mixing, this will allow to apply some results established in Baraud et al. (1999).”
Aggregation for Gaussian regression (2007, background): “4) in regression problems have been obtained by many authors mainly for the model selection case; see, for example, [4, 5, 7, 8, 9, 10, 11, 12, 15, 23, 28, 30, 32, 42] and the references cited in these works.”