The finite sample properties of sparse M-estimators with pseudo-observations View Full Text


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Article Info

DATE

2021-04-08

AUTHORS

Benjamin Poignard, Jean-David Fermanian

ABSTRACT

We provide finite sample properties of general regularized statistical criteria in the presence of pseudo-observations. 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. 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. More... »

PAGES

1-31

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10463-021-00785-4

DOI

http://dx.doi.org/10.1007/s10463-021-00785-4

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1136991727


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