Guaranteed characterization of exact non-asymptotic confidence regions as defined by LSCR and SPS.
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| Title: | Guaranteed characterization of exact non-asymptotic confidence regions as defined by LSCR and SPS. |
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| Authors: | Kieffer, Michel1,2 kieffer@lss.supelec.fr, Walter, Eric1 walter@lss.supelec.fr |
| Source: | Automatica. Feb2014, Vol. 50 Issue 2, p507-512. 6p. |
| Subjects: | Confidence regions (Mathematics), SIMSCRIPT (Computer program language), Parameter estimation, Asymptotic controllability, Numerical analysis |
| Abstract: | Abstract: In parameter estimation, it is often desirable to supplement the estimates with an assessment of their quality. A new family of methods proposed by Campi et al. for this purpose is particularly attractive, as it makes it possible to obtain exact, non-asymptotic confidence regions under mild assumptions on the noise distribution. A bottleneck of this approach, however, is the numerical characterization of these confidence regions. So far, it has been carried out by gridding, which provides no guarantee as to its results and is only applicable to low dimensional spaces. This paper shows how interval analysis can contribute to removing this bottleneck. [Copyright &y& Elsevier] |
| Copyright of Automatica is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 94405588 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Guaranteed characterization of exact non-asymptotic confidence regions as defined by LSCR and SPS. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Kieffer%2C+Michel%22">Kieffer, Michel</searchLink><relatesTo>1,2</relatesTo><i> kieffer@lss.supelec.fr</i><br /><searchLink fieldCode="AR" term="%22Walter%2C+Eric%22">Walter, Eric</searchLink><relatesTo>1</relatesTo><i> walter@lss.supelec.fr</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Automatica%22">Automatica</searchLink>. Feb2014, Vol. 50 Issue 2, p507-512. 6p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Confidence+regions+%28Mathematics%29%22">Confidence regions (Mathematics)</searchLink><br /><searchLink fieldCode="DE" term="%22SIMSCRIPT+%28Computer+program+language%29%22">SIMSCRIPT (Computer program language)</searchLink><br /><searchLink fieldCode="DE" term="%22Parameter+estimation%22">Parameter estimation</searchLink><br /><searchLink fieldCode="DE" term="%22Asymptotic+controllability%22">Asymptotic controllability</searchLink><br /><searchLink fieldCode="DE" term="%22Numerical+analysis%22">Numerical analysis</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Abstract: In parameter estimation, it is often desirable to supplement the estimates with an assessment of their quality. A new family of methods proposed by Campi et al. for this purpose is particularly attractive, as it makes it possible to obtain exact, non-asymptotic confidence regions under mild assumptions on the noise distribution. A bottleneck of this approach, however, is the numerical characterization of these confidence regions. So far, it has been carried out by gridding, which provides no guarantee as to its results and is only applicable to low dimensional spaces. This paper shows how interval analysis can contribute to removing this bottleneck. [Copyright &y& Elsevier] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Automatica is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1016/j.automatica.2013.11.010 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 6 StartPage: 507 Subjects: – SubjectFull: Confidence regions (Mathematics) Type: general – SubjectFull: SIMSCRIPT (Computer program language) Type: general – SubjectFull: Parameter estimation Type: general – SubjectFull: Asymptotic controllability Type: general – SubjectFull: Numerical analysis Type: general Titles: – TitleFull: Guaranteed characterization of exact non-asymptotic confidence regions as defined by LSCR and SPS. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Kieffer, Michel – PersonEntity: Name: NameFull: Walter, Eric IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 02 Text: Feb2014 Type: published Y: 2014 Identifiers: – Type: issn-print Value: 00051098 Numbering: – Type: volume Value: 50 – Type: issue Value: 2 Titles: – TitleFull: Automatica Type: main |
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