Analysis of mixture data with partial least squares
References (9)
A note on polynomial response functions for mixtures
Biometrica
(1971)Soft modeling. The basic design and some extensions
- et al.
Multivariate data analysis in chemistry
There are more references available in the full text version of this article.
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