Nonparametric Bootstrap Estimation for Implicitly Weighted Robust Regression
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F17%3A00475090" target="_blank" >RIV/67985807:_____/17:00475090 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Nonparametric Bootstrap Estimation for Implicitly Weighted Robust Regression
Original language description
Implicitly weighted robust regression estimators for linear and nonlinear regression models include linear and nonlinear versions of the least trimmed squares and least weighted squares. After recalling known facts about these estimators, a nonparametric bootstrap procedure is proposed in this paper for estimates of their variances. These bootstrap estimates are elaborated for both the linear and nonlinear model. Practical contributions include several examples investigating the performance of the nonlinear least weighted squares estimator and comparing it with the classical least squares also by means of the variance estimates. Another theoretical novelty is a proposal of a two-stage version of the nonlinear least weighted squares estimator with adaptive (data-dependent) weights.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10103 - Statistics and probability
Result continuities
Project
<a href="/en/project/GA17-01251S" target="_blank" >GA17-01251S: Metalearning for Extraction of Rules with Numerical Consequents</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings ITAT 2017: Information Technologies - Applications and Theory
ISBN
978-1974274741
ISSN
1613-0073
e-ISSN
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Number of pages
8
Pages from-to
78-85
Publisher name
Technical University & CreateSpace Independent Publishing Platform
Place of publication
Aachen & Charleston
Event location
Martinské hole
Event date
Sep 22, 2017
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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