It is still widely unknown in chemometrics that the statistical analysis of compositional data requires fundamentally different tools than a similar analysis of unconstrained data. This article examines the problems that potentially occur when one performs a partial least squares (PLS) analysis on compositional data and suggests logcontrast partial least squares (LCPLS) as an alternative.
|Number of pages||14|
|Journal||Chemometrics and Intelligent Laboratory Systems|
|State||Published - Nov 1995|
Bibliographical noteFunding Information:
During the course of this research Professor Rayens was supported by NSF grant ATM-9108177.
- Compositional data
- Partial least squares
ASJC Scopus subject areas
- Analytical Chemistry
- Process Chemistry and Technology
- Computer Science Applications