Comparison of principal components regression and partial least squares regression through generic simulations of complex mixtures

By Peter D. Wentzell, Lorenzo Vega Montoto. 2003

194 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Biomedical Engineering, Industrial and Manufacturing Engineering

View Paper: https://www.semanticscholar.org/paper/723de4d686d4ab164b6f26f658fbe3a6b9b5f2e6

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Analytical Chemistry

1. Boaz Nadler
2. Lucka Kajfez-Bogataj
3. Ronald R. Coifman
4. Klemen Bergant
5. David J. Biagioni
6. Shira Kritchman

In Biomedical Engineering

1. Lucka Kajfez-Bogataj
2. Ronald R. Coifman
3. Boaz Nadler
4. Klemen Bergant

In Industrial and Manufacturing Engineering

1. Lucka Kajfez-Bogataj
2. Ronald R. Coifman
3. Boaz Nadler
4. Klemen Bergant

Citations in the corpus

• N–PLS regression as empirical downscaling tool in climate change studies (2005, result): “dance to the results in literature (de Jong, 1993; Wentzell and Montoto, 2003 ), where the performance of PCR and two-dimensional PLS methods are compared.”
• The prediction error in CLS and PLS: the importance of feature selection prior to multivariate calibration (2005, methodology): “Wentzell and Vega-Montoto [10] also made an extensive numerical comparison of PLS and PCR with simulated data containing many components.”