Introduction to Multivariate Calibration A Practical Approach /

This book offers an introductory-level guide to the complex field of multivariate analytical calibration, with particular emphasis on real applications such as near infrared spectroscopy. It presents intuitive descriptions of mathematical and statistical concepts, illustrated with a wealth of figure...

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Bibliographic Details
Main Author: Olivieri, Alejandro C. (Author)
Corporate Author: SpringerLink (Online service)
Format: e-Book
Language:English
Published: Cham : Springer International Publishing : 2018.
Imprint: Springer,
Edition:1st ed. 2018.
Subjects:
Analytical chemistry.
Statistics .
Analytical Chemistry.
Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
Online Access:Full-text access
Table of Contents:
  • Chapter1: Chemometrics and multivariate calibration
  • Chapter2: The classical least-squares model
  • Chapter3: The inverse least-squares model
  • Chapter4: Principal component analysis
  • Chapter5: Principal component regression
  • Chapter6: The optimum number of latent variables
  • Chapter7: The partial least-squares model
  • Chapter8: Comparison of multivariate models
  • Chapter9: Data pre-processing. Part 1: samples and sensors
  • Chapter10: Data pre-processing. Part 2: mathematical filters.-Chapter11: Analytical figures of merit
  • Chapter12: MVC1: a software for multivariate calibration
  • Chapter13: Non-linearity and artificial neural networks
  • Chapter14: Solutions to exercises.

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