2016Journal of ChemometricsOpen access

The chemometrics revolution re‐examined

Steven D. Brown

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Abstract

A historical perspective of the development of chemometrics as a field is given. Special attention is given to early workers in the analysis and modeling of chemical data in an effort to show how the field evolved from a broad, mostly statistical discipline to a more narrowly focused field focused on multivariate predictive analysis. A discussion of the relationships of chemometrics with statistics, chemical modeling, and analytical chemistry is provided to show how early conflicts have shaped and continue to shape the field. The author considers the state of the field now and makes suggestions for the way in which chemometrics should change to remain vital in the rapidly changing area of data analysis.

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A historical perspective of the development of chemometrics as a field is given. Special attention is given to early workers in the analysis and modeling of chemical data in an effort to show how the field evolved from a broad, mostly statistical discipline to a more narrowly focused field focused on multivariate predictive analysis. A discussion of the relationships of chemometrics with statistics, chemical modeling, and analytical chemistry is provided to show how early conflicts have shaped and continue to shape the field. The author considers the state of the field now and makes suggestions for the way in which chemometrics should change to remain vital in the rapidly changing area of data analysis.

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Available abstract

A historical perspective of the development of chemometrics as a field is given. Special attention is given to early workers in the analysis and modeling of chemical data in an effort to show how the field evolved from a broad, mostly statistical discipline to a more narrowly focused field focused on multivariate predictive analysis. A discussion of the relationships of chemometrics with statistics, chemical modeling, and analytical chemistry is provided to show how early conflicts have shaped and continue to shape the field. The author considers the state of the field now and makes suggestions for the way in which chemometrics should change to remain vital in the rapidly changing area of data analysis.

Key concepts: Chemometrics, Field (mathematics), Perspective (graphical), Computer science, Data science, Statistical analysis, Multivariate statistics, Management science

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