Multivariate calibration.
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Summary
The bases of multivariate calibration are presented with special attention to some points usually not considered or underevaluated, i.e., the sampling design, the number of samples necessary to obtain a reliable regression model, the effect of noisy predictors, and the significance of the parameters used to evaluate the performance ability of the regression model.
- Type
- review
- Published
- 2007-03-29
- Cited by
- 1,841
- References
- 0
- OpenAlex
- https://openalex.org/W4237144788
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:10927650
Keywords
Multivariate statistics, Calibration, Statistics, Sampling (signal processing), Regression analysis
References
- Multivariate Calibration
- Computer Aided Design of Experiments
- Cross-Validatory Estimation of the Number of Components in Factor and Principal Components Models
- Estimating Optimal Transformations for Multiple Regression and Correlation
- Handbook of Chemometrics and Qualimetrics: Part B
- Statistics: Methods and Applications
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