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Multivariate data analysis (MVDA) in landfill research
Luleå University of Technology.
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Geosciences and Environmental Engineering.
1996 (English)In: Proceedings of the 12th International Conference on Solid Waste Technology and Management, Indiana University of Pennsylvania, 1996Conference paper (Refereed)
Abstract [en]

Multivariate data analysis (MVDA), a new statistical approach in terms of landfill research, was performed on the evaluation of three investigations. It gains advantage over classical statistical methods when multiple variables and their interactions have to be considered. In addition, it is tolerant for incomplete datasets. MVDA techniques as follows were applied: principal component analysis (PCA), partial least squares modelling (PLS) and partial least squares discriminant analysis (PLS-DA). The interrelationships among variables as well as variation between observations could be examined and illustrated by a few plots.

Place, publisher, year, edition, pages
Indiana University of Pennsylvania, 1996.
International Conference on Solid Waste Technology. Proceedi, ISSN 1091-8043
Research subject
Waste Science and Technology
URN: urn:nbn:se:ltu:diva-34382Local ID: 89018260-4fd8-11dc-98a3-000ea68e967bOAI: diva2:1007633
International Conference on Solid Waste Technology and Management : 17/11/1996 - 20/11/1996
Godkänd; 1996; 20070821 (pafi)Available from: 2016-09-30 Created: 2016-09-30Bibliographically approved

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