Clusterwise PLS regression on a stochastic process

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Bibliographic Details
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]
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Database: Engineering Source
Description
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]
ISSN:01679473
DOI:10.1016/j.csda.2004.05.002