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Clusterwise PLS regression on a stochastic process

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Title: Clusterwise PLS regression on a stochastic process
Authors: Preda, C.1 cpreda@univ-lille2.fr, Saporta, G.2 saporta@cnam.fr
Source: Computational Statistics & Data Analysis. Apr2005, Vol. 49 Issue 1, p99-108. 10p.
Subjects: Stochastic processes, Regression analysis, Estimation theory, Probability theory
Abstract: Abstract: The clusterwise linear regression is studied when the set of predictor variables forms a -continuous stochastic process. For each cluster the estimators of the regression coefficients are given by partial least square regression. The number of clusters is treated as unknown and the convergence of the clusterwise algorithm is discussed. The approach is compared with other methods via an application on stock-exchange data. [Copyright &y& Elsevier]
Copyright of Computational Statistics & Data Analysis is the property of Elsevier B.V. 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
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Header DbId: egs
DbLabel: Engineering Source
An: 16511792
AccessLevel: 6
PubType: Periodical
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  Data: Abstract: The clusterwise linear regression is studied when the set of predictor variables forms a -continuous stochastic process. For each cluster the estimators of the regression coefficients are given by partial least square regression. The number of clusters is treated as unknown and the convergence of the clusterwise algorithm is discussed. The approach is compared with other methods via an application on stock-exchange data. [Copyright &y& Elsevier]
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  Data: <i>Copyright of Computational Statistics & Data Analysis is the property of Elsevier B.V. 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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        Value: 10.1016/j.csda.2004.05.002
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      – Code: eng
        Text: English
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        PageCount: 10
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      – SubjectFull: Stochastic processes
        Type: general
      – SubjectFull: Regression analysis
        Type: general
      – SubjectFull: Estimation theory
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      – TitleFull: Clusterwise PLS regression on a stochastic process
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            NameFull: Preda, C.
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              Text: Apr2005
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