Academic Journal
Submitted to the Annals of Statistics AGGREGATION FOR GAUSSIAN REGRESSION
العنوان: | Submitted to the Annals of Statistics AGGREGATION FOR GAUSSIAN REGRESSION |
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المؤلفون: | Florentina Bunea, Re B. Tsybakov, Marten H |
المساهمون: | The Pennsylvania State University CiteSeerX Archives |
المصدر: | http://eprints.pascal-network.org/archive/00003857/01/annals_revision_4.pdf. |
المجموعة: | CiteSeerX |
مصطلحات موضوعية: | aggregation, lasso estimator, minimax risk, model selection, model averaging, nonparametric regression, oracle inequalities, penalized least squares |
الوصف: | This paper studies statistical aggregation procedures in the regression setting. A motivating factor is the existence of many different methods of estimation, leading to possibly competing estimators. We consider here three different types of aggregation: model selection (MS) aggregation, convex (C) aggregation and linear (L) aggregation. The objective of (MS) is to select the optimal single estimator from the list; that of (C) is to select the optimal convex combination of the given estimators; and that of (L) is to select the optimal linear combination of the given estimators. We are interested in evaluating the rates of convergence of the excess risks of the estimators obtained by these procedures. Our approach is motivated by recent minimax results in [34, 40]. There exist competing aggregation procedures achieving optimal convergence rates for each of the (MS), (C) and (L) cases separately. Since these procedures are not directly comparable with each other, we suggest an alternative solution. We prove that all the three optimal rates, as well as those for the newly introduced (S) |
نوع الوثيقة: | text |
وصف الملف: | application/pdf |
اللغة: | English |
Relation: | http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.422.5982; http://eprints.pascal-network.org/archive/00003857/01/annals_revision_4.pdf |
الاتاحة: | http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.422.5982 http://eprints.pascal-network.org/archive/00003857/01/annals_revision_4.pdf |
Rights: | Metadata may be used without restrictions as long as the oai identifier remains attached to it. |
رقم الانضمام: | edsbas.EF8176A7 |
قاعدة البيانات: | BASE |
الوصف غير متاح. |