Theory of medium-rank second-order calibration with restricted-Tucker models
✍ Scribed by Age K. Smilde; Yongdong Wang; Bruce R. Kowalski
- Publisher
- John Wiley and Sons
- Year
- 1994
- Tongue
- English
- Weight
- 951 KB
- Volume
- 8
- Category
- Article
- ISSN
- 0886-9383
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✦ Synopsis
If an analytical instrument or instrumental method gives a response matrix when analyzing a pure analyte, the instrument or instrumental method is called a second-order method. Second-order methods that generate a response matrix for a pure analyte of rank one are called rank-one second-order methods.
If the response matrix of a pure analyte is not rank one, essentially two cases exist: medium rank (between two and five) and high rank (greater than five). Subsequently, medium-and high-rank second-order calibration tries to use medium-and high-rank second-order methods to analyze for analytes of interest in a mixture. A particular advantage of second-order methods is the ability to analyze for analytes of interest in a mixture which contains unknown interferences. Keeping this advantage is the challenge on moving away from rank-one second-order calibration methods. In this paper a medium-rank secondorder calibration method is proposed based on least-squares restricted Tucker models. With this method the second-order advantage is retained.