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Introduction to multivariate calibra...
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Olivieri, Alejandro C.
Introduction to multivariate calibrationa practical approach /
Record Type:
Electronic resources : Monograph/item
Title/Author:
Introduction to multivariate calibrationby Alejandro C. Olivieri.
Reminder of title:
a practical approach /
Author:
Olivieri, Alejandro C.
Published:
Cham :Springer International Publishing :2018.
Description:
xvii, 243 p. :ill. (some col.), digital ;24 cm.
Contained By:
Springer eBooks
Subject:
Chemometrics.
Online resource:
http://dx.doi.org/10.1007/978-3-319-97097-4
ISBN:
9783319970974$q(electronic bk.)
Introduction to multivariate calibrationa practical approach /
Olivieri, Alejandro C.
Introduction to multivariate calibration
a practical approach /[electronic resource] :by Alejandro C. Olivieri. - Cham :Springer International Publishing :2018. - xvii, 243 p. :ill. (some col.), digital ;24 cm.
Chapter1: Chemometrics and multivariate calibration -- Chapter2: The classical least-squares model -- Chapter3: The inverse least-squares model -- Chapter4: Principal component analysis -- Chapter5: Principal component regression -- Chapter6: The optimum number of latent variables -- Chapter7: The partial least-squares model -- Chapter8: Comparison of multivariate models -- Chapter9: Data pre-processing. Part 1: samples and sensors -- Chapter10: Data pre-processing. Part 2: mathematical filters -- Chapter11: Analytical figures of merit -- Chapter12: MVC1: a software for multivariate calibration -- Chapter13: Non-linearity and artificial neural networks -- Chapter14: Solutions to exercises.
This book offers an introductory-level guide to the complex field of multivariate analytical calibration, with particular emphasis on real applications such as near infrared spectroscopy. It presents intuitive descriptions of mathematical and statistical concepts, illustrated with a wealth of figures and diagrams, and consistently highlights physicochemical interpretation rather than mathematical issues. In addition, it describes an easy-to-use and freely available graphical interface, together with a variety of appropriate examples and exercises. Lastly, it discusses recent advances in the field (figures of merit, detection limit, non-linear calibration, method comparison), together with modern literature references.
ISBN: 9783319970974$q(electronic bk.)
Standard No.: 10.1007/978-3-319-97097-4doiSubjects--Topical Terms:
265647
Chemometrics.
LC Class. No.: QD75.4.C45 / O458 2018
Dewey Class. No.: 543.015195
Introduction to multivariate calibrationa practical approach /
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a practical approach /
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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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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 figures and diagrams, and consistently highlights physicochemical interpretation rather than mathematical issues. In addition, it describes an easy-to-use and freely available graphical interface, together with a variety of appropriate examples and exercises. Lastly, it discusses recent advances in the field (figures of merit, detection limit, non-linear calibration, method comparison), together with modern literature references.
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Chemistry and Materials Science (Springer-11644)
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EB QD75.4.C45 O49 2018 2018
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http://dx.doi.org/10.1007/978-3-319-97097-4
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