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Introduction to Multivariate Calibration

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Cover of 'Introduction to Multivariate Calibration'

Table of Contents

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    Book Overview
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    Chapter 1 Chemometrics and Multivariate Calibration
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    Chapter 2 The Classical Least-Squares Model
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    Chapter 3 The Inverse Least-Squares Model
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    Chapter 4 Principal Component Analysis
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    Chapter 5 Principal Component Regression
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    Chapter 6 The Optimum Number of Latent Variables
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    Chapter 7 The Partial Least-Squares Model
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    Chapter 8 Sample and Sensor Selection
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    Chapter 9 Mathematical Pre-processing
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    Chapter 10 Analytical Figures of Merit
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    Chapter 11 MVC1: Software for Multivariate Calibration
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    Chapter 12 Non-linearity and Artificial Neural Networks
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    Chapter 13 Solutions to Exercises
Attention for Chapter 6: The Optimum Number of Latent Variables
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