Non-asymptotic approach to varying coefficient model

In the present paper we consider the varying coefficient model which represents a useful tool for exploring dynamic patterns in many applications. Existing methods typically provide asymptotic evaluation of precision of estimation procedures under the assumption that the number of observations tends to infinity. In practical applications, however, only a finite number of measurements are available. In the present paper we focus on a non-asymptotic approach to the problem. We propose a novel estimation procedure which is based on recent developments in matrix estimation. In particular, for our estimator, we obtain upper bounds for the mean squared and the pointwise estimation errors. The obtained oracle inequalities are non-asymptotic and hold for finite sample size.

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Additional Info

Field Value
Source ISSN: 1935-7524
Author Klopp, Olga, Pensky, Marianna
Maintainer CCSD
Last Updated May 14, 2026, 16:12 (UTC)
Created May 14, 2026, 16:12 (UTC)
Identifier hal-00752131
Language en
Rights https://about.hal.science/hal-authorisation-v1/
contributor Modélisation aléatoire de Paris X (MODAL'X) ; Université Paris Nanterre (UPN)-Centre National de la Recherche Scientifique (CNRS)
creator Klopp, Olga
date 2013-05-14T00:00:00
harvest_object_id 30d2e15a-2856-4a4b-a883-5552fd8d7cc6
harvest_source_id 3374d638-d20b-4672-ba96-a23232d55657
harvest_source_title test moissonnage SELUNE
metadata_modified 2024-06-06T00:00:00
relation info:eu-repo/semantics/altIdentifier/arxiv/1211.3394
set_spec type:ART