Topic
Chemometrics
About: Chemometrics is a research topic. Over the lifetime, 2864 publications have been published within this topic receiving 73032 citations.
Papers published on a yearly basis
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Papers
TL;DR: A recent visit to one of BP’s European technology centers produced a request to develop statistics training for the people in the analytical lab, so a search to see what books were available found this book, a husband and wife pairing of an analytical chemist and a statistician, hard to imagine a much better book for use as the first course with a group of analytical chemists.
Abstract: (2004). Statistics and Chemometrics for Analytical Chemistry. Technometrics: Vol. 46, No. 4, pp. 498-499.
5,241 citations
TL;DR: The multi-way decomposition method PARAFAC is a generalization of PCA to higher order arrays, but some of the characteristics of the method are quite different from the ordinary two-way case.
2,839 citations
TL;DR: In this article, the authors examined partial least squares and principal components regression from a statistical perspective and compared them with other statistical methods intended for those situations, such as variable subset selection and ridge regression.
Abstract: Chemometrics is a field of chemistry that studies the application of statistical methods to chemical data analysis. In addition to borrowing many techniques from the statistics and engineering literatures, chemometrics itself has given rise to several new data-analytical methods. This article examines two methods commonly used in chemometrics for predictive modeling—partial least squares and principal components regression—from a statistical perspective. The goal is to try to understand their apparent successes and in what situations they can be expected to work well and to compare them with other statistical methods intended for those situations. These methods include ordinary least squares, variable subset selection, and ridge regression.
2,565 citations
TL;DR: The paper focuses on the use of principal component analysis in typical chemometric areas but the results are generally applicable.
Abstract: Principal component analysis is one of the most important and powerful methods in chemometrics as well as in a wealth of other areas. This paper provides a description of how to understand, use, and interpret principal component analysis. The paper focuses on the use of principal component analysis in typical chemometric areas but the results are generally applicable.
2,512 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2026 | 1 |
| 2025 | 331 |
| 2024 | 557 |
| 2023 | 693 |
| 2022 | 1,188 |
| 2021 | 225 |