Clustered regression analysis [Elektronisk resurs] / David Lindgren, Lennart Ljung
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Lindgren, David, 1968- (författare)
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Ljung, Lennart, 1946- (författare)
- Linköping : Linköping University Electronic Press, 2002
- Engelska 8 s.
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Serie: LiTH-ISY-R, 1400-3902 ; 2456
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Läs hela texten (Sammanfattning och fulltext från Linköping University Electronic Press)
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- Cluster structure in (multicollinear) data can be utilized by pattern recognition methods in order to find adequate subspaces for nonlinear regression. When regressing a particular severely nonlinear function, it is demonstrated that this approach is superior to polynomial PLS. It is also demonstrated that for nonlinear functions, the choice of regressing explained variables onto the explaining variables, or vice-versa, is not arbitrary. Numerical experiments indicate that the classical statistical model is more powerful than the inverse regression approach.
Indexterm och SAB-rubrik
- Nonlinear regression Subspace regression Inverse regression
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