Clustered Regression Analysis
2002 (English)In: Proceedings of the 41st IEEE Conference on Decision and Control, 2002, 1838-1844 vol.2 p.Conference paper (Refereed)
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.
Place, publisher, year, edition, pages
2002. 1838-1844 vol.2 p.
Nonlinear regression, Subspace regression, Inverse regression
Engineering and Technology Control Engineering
IdentifiersURN: urn:nbn:se:liu:diva-90316DOI: 10.1109/CDC.2002.1184791ISBN: 0-7803-7516-5OAI: oai:DiVA.org:liu-90316DiVA: diva2:613616
41st IEEE Conference on Decision and Control, Las Vegas, NV, USA, December, 2002