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A0460
Title: The finite sample properties of sparse M-estimators with pseudo-observations Authors:  Benjamin Poignard - Osaka University (Japan) [presenting]
Jean-David Fermanian - Ensae-Crest (France)
Abstract: Finite sample properties of general regularized statistical criteria in the presence of pseudo-observations are provided. Under the restricted strong convexity assumption of the unpenalized loss function and regularity conditions on the penalty, we derive non-asymptotic error bounds on the regularized M-estimator that hold with high probability. This penalized framework with pseudo-observations is then applied to the M-estimation of some usual copula-based models. These theoretical results are supported by an empirical study.