000			05919cam a2200565Mi 4500
001			ocn874098247
003			OCoLC
005			20190328114807.0
006			m o d
007			cr |n|||||||||
008			140321s2014 ne ob 001 0 eng d
040			_aIDEBK _beng _erda _epn _cIDEBK _dEBLCP _dOPELS _dN$T _dUKMGB _dYDXCP _dCDX _dOCLCF _dOCLCQ _dDEBSZ _dOCLCQ _dFEM _dITD _dMERER _dOCLCQ _dU3W _dD6H _dE7B _dOTZ _dAU@ _dWYU _dAUD
016	7		_a016709716 _2Uk
019			_a877868296 _a878141465 _a968014193 _a969024797
020			_a1306510996 _q(electronic bk.)
020			_a9781306510998 _q(electronic bk.)
020			_a9780124104082 _q(electronic bk.)
020			_a0124104088 _q(electronic bk.)
020			_a9780124104549 _q(electronic bk.)
020			_a0124104541 _q(electronic bk.)
035			_a(OCoLC)874098247 _z(OCoLC)877868296 _z(OCoLC)878141465 _z(OCoLC)968014193 _z(OCoLC)969024797
050		4	_aQC39 _b.O384 2014
072		7	_aSCI _x013010 _2bisacsh
082	0	4	_a621.372
100	1		_aOlivieri, Alejandro.
245	1	0	_aPractical three-way calibration / _h[electronic resource] _cAlejandro C. Olivieri and Graciela M. Escandar.
264		1	_aAmsterdam : _bElsevier, _c2014.
300			_a1 online resource
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _2rda
588	0		_aPrint version record.
520			_aPractical 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.
504			_aIncludes bibliographical references and index.
505	0		_aFront 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.
505	8		_a2.6 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.
505	8		_a4.1 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.
505	8		_a5.8 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.
505	8		_a7.1 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.
650		0	_aChemometrics.
650		0	_aCalibration.
650		7	_aSCIENCE _xChemistry _xAnalytic. _2bisacsh
650		7	_aCalibration. _2fast _0(OCoLC)fst00844249
650		7	_aChemometrics. _2fast _0(OCoLC)fst01736550
655		4	_aElectronic books.
700	1		_aEscandar, Graciela M.
776	0	8	_iPrint version: _z9781306510998
856	4	0	_3ScienceDirect _uhttp://www.sciencedirect.com/science/book/9780124104082
999			_c246894 _d246894