05919cam a2200565Mi 4500 ocn874098247 OCoLC 20190328114807.0 m o d cr |n||||||||| 140321s2014 ne ob 001 0 eng d IDEBK eng rda pn IDEBK EBLCP OPELS N$T UKMGB YDXCP CDX OCLCF OCLCQ DEBSZ OCLCQ FEM ITD MERER OCLCQ U3W D6H E7B OTZ AU@ WYU AUD 016709716 Uk 877868296 878141465 968014193 969024797 1306510996 (electronic bk.) 9781306510998 (electronic bk.) 9780124104082 (electronic bk.) 0124104088 (electronic bk.) 9780124104549 (electronic bk.) 0124104541 (electronic bk.) (OCoLC)874098247 (OCoLC)877868296 (OCoLC)878141465 (OCoLC)968014193 (OCoLC)969024797 QC39 .O384 2014 SCI 013010 bisacsh 621.372 Olivieri, Alejandro. Practical three-way calibration / [electronic resource] Alejandro C. Olivieri and Graciela M. Escandar. Amsterdam : Elsevier, 2014. 1 online resource text txt rdacontent computer c rdamedia online resource cr rdacarrier text file rda Print version record. Practical Three-Way Calibration is an introductory-level guide to the complex field of analytical calibration with three-way instrumental data. With minimal use of mathematical/statistical expressions, it walks the reader through the analytical methodologies with helpful images and step-by-step explanations. Unlike other books on the subject, there is no need for prior programming experience and no need to learn programming languages. Easy-to-use graphical interfaces and intuitive descriptions of mathematical and statistical concepts make three-way calibration methodologies accessible to analytical chemists and scientists in a wide range of disciplines in industry and academia. Numerous detailed examples of slowly increasing complexity Exposure to several different data sets and techniques through figures and diagrams Computer program screenshots for easy learning without prior knowledge of programming languages Minimal use of mathematical/statistical expressions. Includes bibliographical references and index. Front Cover; Practical Three-Way Calibration; Copyright; Dedication; Contents; Preface; References; Foreword; Acknowledgments; Chapter 1 -- Calibration Scenarios; 1.1 Calibration; 1.2 Univariate calibration; 1.3 Multivariate calibration; 1.4 Nomenclature for data and calibrations; 1.5 Nomenclature for constituents and samples; 1.6 Multiway calibration; 1.7 Why multiway calibration?; 1.8 Analytical advantages; References; Chapter 2 -- Data Properties; 2.1 Data properties; 2.2 Bilinear data; 2.3 Normalization and concentration effects; 2.4 A word of caution on bilinearity; 2.5 Nonbilinear data. 2.6 Trilinear data2.7 Nontrilinear data; 2.8 Transforming three-way data into matrix data; 2.9 Normalization and concentration effects; 2.10 Classification of three-way data; 2.11 Importance of classifying three-way data; References; Chapter 3 -- Experimental Three-way/Second-order Data; 3.1 Generation of three-way data; 3.2 Matrix fluorescence spectroscopy; 3.3 Chromatography with spectral detection; 3.4 Other second-order instrumental data; 3.5 Data organization in files; 3.6 Samples for calibration and validation; References; Chapter 4 -- The MVC2 Software. 4.1 Methods, models, algorithms and software4.2 The MVC2 software; 4.3 The MVC2 data examples; 4.4 The EEFM_data example; 4.5 Plotting EEFM_data matrices; 4.6 The LCDAD_data example; 4.7 Plotting LCDAD_data matrices; 4.8 Further MVC2 features; References; Chapter 5 -- Parallel Factor Analysis: Trilinear Data; 5.1 Trilinear modeling and decomposition; 5.2 Uniqueness and the second-order advantage; 5.3 Processing the EEFM_data example; 5.4 PARAFAC analysis of a test sample; 5.5 Estimating the number of components; 5.6 Analyte quantitation in the test sample; 5.7 Analysis of the remaining samples. 5.8 Profiles for potential interferents5.9 Further processing options; 5.10 Multiple-sample processing; 5.11 Concluding remarks; 5.12 Homework 1; 5.13 Homework 2; References; Chapter 6 -- Analytical Figures of Merit; 6.1 Definition of figure of merit; 6.2 Importance of analytical figures of merit; 6.3 Sensitivity; 6.4 Selectivity; 6.5 Analytical sensitivity; 6.6 Prediction uncertainty; 6.7 Limit of detection; 6.8 Limit of quantitation; 6.9 The complete PARAFAC report; 6.10 Final considerations; References; Chapter 7 -- Parallel Factor Analysis: Nontrilinear Data of Type 1. 7.1 An apparent contradiction7.2 Description of the data set; 7.3 PARAFAC study of a test sample; 7.4 Increasing the number of PARAFAC components; 7.5 Study of the remaining samples; 7.6 Other separation data and what to do; 7.7 A PARAFAC variant for chromatographic data; 7.8 PARAFAC2 calibration with the LCDAD_data; 7.9 Chromatographic alignment; 7.10 Homework; References; Chapter 8 -- Multivariate Curve Resolution-Alternating Least-Squares; 8.1 Multivariate curve resolution-alternating least-squares; 8.2 Estimating the number of components; 8.3 MCR-ALS initialization; 8.4 Constraints. Chemometrics. Calibration. SCIENCE Chemistry Analytic. bisacsh Calibration. fast (OCoLC)fst00844249 Chemometrics. fast (OCoLC)fst01736550 Electronic books. Escandar, Graciela M. Print version: 9781306510998 ScienceDirect http://www.sciencedirect.com/science/book/9780124104082 246894 246894