SCREAM: A novel method for multi-way regression problems with shifts and shape changes in one mode

Chemometrics and Intelligent Laboratory Systems

Volumn 129, Issue , 2013, Pages 64-75

  Marini, Federico ^a   Bro, Rasmus ^b  

^a SAPIENZA UNIVERSITY OF ROME   (Italy)

^b UNIVERSITY OF COPENHAGEN   (Denmark)

Author keywords

Multi way calibration; Multi way covariate regression; PARAFAC2; Principal covariates regression (PCovR); SCREAM (Shifted Covariate REgression Analysis for Multi way data)

Indexed keywords

4 HYDROXYBENZOIC ACID; CAFFEIC ACID; OLIVE OIL; SUGAR; SYRINGIC ACID; VANILLIC ACID;

ACIDITY; ALGORITHM; ARTICLE; CALIBRATION; CONCENTRATION (PARAMETERS); DATA ANALYSIS; HIGH PERFORMANCE LIQUID CHROMATOGRAPHY; MASS FRAGMENTOGRAPHY; MATHEMATICAL COMPUTING; PARTIAL LEAST SQUARES REGRESSION; PREDICTION; PRIORITY JOURNAL; REGRESSION ANALYSIS; SHIFTED COVARIATE REGRESSION ANALYSIS FOR MULTIWAY DATA; WINE;

EID: 84888834970     PISSN: 01697439     EISSN: 18733239     Source Type: Journal    
DOI: 10.1016/j.chemolab.2013.09.012     Document Type: Article

References (21)

1. Harshman R.A. Foundations of the PARAFAC procedure: models and conditions for an 'explanatory' multi-modal factor analysis. UCLA Work. Pap. Phon. 1970, 16:1-84.
2. Bro R. PARAFAC. Tutorial and applications. Chemometr. Intell. Lab. Syst. 1997, 38:149-171.
3. Bro R. Multiway calibration. Multilinear PLS. J. Chemometr. 1996, 10:47-61.
4. Harshman R.A. PARAFAC2: mathematical and technical notes. UCLA Work. Pap. Phon. 1972, 22:30-47.
5. Bro R., Andersson C.A., Kiers H.A.L. PARAFAC2 - part II. Modeling chromatographic data with retention time shifts. J. Chemometr. 1999, 13:295-309.
6. Skov T., Bro R. A new approach for modelling sensor based data. Sensors Actuators B 2005, 106:719-729.
7. Amigo J.M., Skov T., Coello J., Maspoch S., Bro R. Solving GC-MS problems with PARAFAC2. Trends Anal. Chem. 2008, 27:714-725.
8. Wiberg K., Jacobsson S.P. Parallel factor analysis of HPLC-DAD data for binary mixtures of lidocaine and prilocaine with different levels of chromatographic separation. Anal. Chim. Acta. 2004, 514:203-209.
9. Wise B.M., Gallagher N.B., Martin E.B. Application of PARAFAC2 to fault detection and diagnosis in semiconductor etch. J. Chemometr. 2001, 15:285-298.
10. de Jong S., Kiers H.A.L. Principal covariates regression. Part 1. Theory. Chemometr. Intell. Lab. Syst. 1992, 14:155-164.
11. Smilde A.K., Kiers H.A.L. Multiway covariates regression models. J. Chemometr. 1999, 13:31-48.
12. Kiers H.A.L., ten Berge J.M.F., Bro R. PARAFAC2 - part I. A direct fitting algorithm for the PARAFAC2 model. J. Chemometr. 1999, 13:275-294.
13. Bro R. Multi-way Analysis in the Food Industry. Models, Algorithms, and Applications 1998, (Ph.D. thesis), University of Amsterdam (NL), [Available at http://www.models.life.ku.dk/research/theses/ (Last accessed July 13th 2013)].
14. Marini F., D'Aloise A., Bucci R., Buiarelli F., Magrì A.D., Magrì A.L. Fast analysis of 4 phenolic acids in olive oil by HPLC-DAD and chemometrics. Chemometr. Intell. Lab. Syst. 2011, 106:142-149.
15. Skov T., Ballabio D., Bro R. Multiblock variance partitioning. A new approach for comparing variation in multiple data blocks. Anal. Chim. Acta. 2008, 615:18-29.
16. Snee RD R.D. Validation of regression models: methods and examples. Technometrics 1977, 19:415-418.
17. Bro R. Exploratory study of sugar production using fluorescence spectroscopy and multi-way analysis. Chemometr. Intell. Lab. Syst. 1999, 46:133-147.
18. Tomasi G., Savorani F., Engelsen S.B. iCoshift: an effective tool for the alignment of chromatographic data. J. Chromatogr. A 2011, 1218:7832-7840.
19. Gower J.C. Generalized procrustes analysis. Psychometrika 1975, 40:33-51.
20. Kiers H.A.L. An alternating least squares algorithm for PARAFAC2 and three-way DEDICOM. Comput. Stat. Data Anal. 1993, 16:103-118.
21. Vervloet M., Van Deun K., Van den Noortgate W., Ceulemans E. On the selection of the weighting parameter value in Principal Covariates Regression. Chemometr. Intell. Lab. Syst. 2013, 123:36-43.