Preface xvii

PART I INTRODUCTION 1

1 What is Chemometrics? 3

1.1 Subject of Chemometrics, 3

1.2 Historical Digression, 5

2 What the Book Is About? 8

2.1 Useful Hints, 8

2.2 Book Syllabus, 9

2.3 Notations, 10

3 Installation of Chemometrics Add-In 11

3.1 Installation, 11

3.2 General Information, 14

4 Further Reading on Chemometrics 15

4.1 Books, 15

4.1.1 The Basics, 15

4.1.2 Chemometrics, 16

4.1.3 Supplements, 16

4.2 The Internet, 17

4.2.1 Tutorials, 17

4.3 Journals, 17

4.3.1 Chemometrics, 17

4.3.2 Analytical, 18

4.3.3 Mathematical, 18

4.4 Software, 18

4.4.1 Specialized Packages, 18

4.4.2 General Statistic Packages, 19

4.4.3 Free Ware, 19

PART II THE BASICS 21

5 Matrices and Vectors 23

5.1 The Basics, 23

5.1.1 Matrix, 23

5.1.2 Simple Matrix Operations, 24

5.1.3 Matrices Multiplication, 25

5.1.4 Square Matrix, 26

5.1.5 Trace and Determinant, 27

5.1.6 Vectors, 28

5.1.7 Simple Vector Operations, 29

5.1.8 Vector Products, 29

5.1.9 Vector Norm, 30

5.1.10 Angle Between Vectors, 30

5.1.11 Vector Representation of a Matrix, 30

5.1.12 Linearly Dependent Vectors, 31

5.1.13 Matrix Rank, 31

5.1.14 Inverse Matrix, 31

5.1.15 Pseudoinverse, 32

5.1.16 Matrix-Vector Product, 33

5.2 Advanced Information, 33

5.2.1 Systems of Linear Equations, 33

5.2.2 Bilinear and Quadratic Forms, 34

5.2.3 Positive Definite Matrix, 34

5.2.4 Cholesky Decomposition, 34

5.2.5 Polar Decomposition, 34

5.2.6 Eigenvalues and Eigenvectors, 35

5.2.7 Eigenvalues, 35

5.2.8 Eigenvectors, 35

5.2.9 Equivalence and Similarity, 36

5.2.10 Diagonalization, 37

5.2.11 Singular Value Decomposition (SVD), 37

5.2.12 Vector Space, 38

5.2.13 Space Basis, 39

5.2.14 Geometric Interpretation, 39

5.2.15 Nonuniqueness of Basis, 39

5.2.16 Subspace, 40

5.2.17 Projection, 40

6 Statistics 42

6.1 The Basics, 42

6.1.1 Probability, 42

6.1.2 Random Value, 43

6.1.3 Distribution Function, 43

6.1.4 Mathematical Expectation, 44

6.1.5 Variance and Standard Deviation, 44

6.1.6 Moments, 44

6.1.7 Quantiles, 45

6.1.8 Multivariate Distributions, 45

6.1.9 Covariance and Correlation, 45

6.1.10 Function, 46

6.1.11 Standardization, 46

6.2 Main Distributions, 46

6.2.1 Binomial Distribution, 46

6.2.2 Uniform Distribution, 47

6.2.3 Normal Distribution, 48

6.2.4 Chi-Squared Distribution, 50

6.2.5 Student's Distribution, 52

6.2.6 F-Distribution, 53

6.2.7 Multivariate Normal Distribution, 54

6.2.8 Pseudorandom Numbers, 55

6.3 Parameter Estimation, 56

6.3.1 Sample, 56

6.3.2 Outliers and Extremes, 56

6.3.3 Statistical Population, 56

6.3.4 Statistics, 57

6.3.5 Sample Mean and Variance, 57

6.3.6 Sample Covariance and Correlation, 58

6.3.7 Order Statistics, 59

6.3.8 Empirical Distribution and Histogram, 60

6.3.9 Method of Moments, 61

6.3.10 The Maximum Likelihood Method, 62

6.4 Properties of the Estimators, 62

6.4.1 Consistency, 62

6.4.2 Bias, 63

6.4.3 Effectiveness, 63

6.4.4 Robustness, 63

6.4.5 Normal Sample, 64

6.5 Confidence Estimation, 64

6.5.1 Confidence Region, 64

6.5.2 Confidence Interval, 65

6.5.3 Example of a Confidence Interval, 65

6.5.4 Confidence Intervals for the Normal Distribution, 65

6.6 Hypothesis Testing, 66

6.6.1 Hypothesis, 66

6.6.2 Hypothesis Testing, 66

6.6.3 Type I and Type II Errors, 67

6.6.4 Example, 67

6.6.5 Pearson's Chi-Squared Test, 67

6.6.6 F-Test, 69

6.7 Regression, 70

6.7.1 Simple Regression, 70

6.7.2 The Least Squares Method, 71

6.7.3 Multiple Regression, 72

Conclusion, 73

7 Matrix Calculations in Excel 74

7.1 Basic Information, 74

7.1.1 Region and Language, 74

7.1.2 Workbook, Worksheet, and Cell, 76

7.1.3 Addressing, 77

7.1.4 Range, 78

7.1.5 Simple Calculations, 78

7.1.6 Functions, 78

7.1.7 Important Functions, 81

7.1.8 Errors in Formulas, 85

7.1.9 Formula Dragging, 86

7.1.10 Create a Chart, 87

7.2 Matrix Operations, 88

7.2.1 Array Formulas, 88

7.2.2 Creating and Editing an Array Formula, 90

7.2.3 Simplest Matrix Operations, 91

7.2.4 Access to the Part of a Matrix, 91

7.2.5 Unary Operations, 93

7.2.6 Binary Operations, 95

7.2.7 Regression, 95

7.2.8 Critical Bug in Excel 2003, 99

7.2.9 Virtual Array, 99

7.3 Extension of Excel Possibilities, 100

7.3.1 VBA Programming, 100

7.3.2 Example, 101

7.3.3 Macro Example, 103

7.3.4 User-Defined Function Example, 104

7.3.5 Add-Ins, 105

7.3.6 Add-In Installation, 106

Conclusion, 107

8 Projection Methods in Excel 108

8.1 Projection Methods, 108

8.1.1 Concept and Notation, 108

8.1.2 PCA, 109

8.1.3 PLS, 110

8.1.4 Data Preprocessing, 111

8.1.5 Didactic Example, 112

8.2 Application of Chemometrics Add-In, 113

8.2.1 Installation, 113

8.2.2 General, 113

8.3 PCA, 114

8.3.1 ScoresPCA, 114

8.3.2 LoadingsPCA, 114

8.4 PLS, 116

8.4.1 ScoresPLS, 116

8.4.2 UScoresPLS, 117

8.4.3 LoadingsPLS, 118

8.4.4 WLoadingsPLS, 119

8.4.5 QLoadingsPLS, 120

8.5 PLS2, 121

8.5.1 ScoresPLS2, 121

8.5.2 UScoresPLS2, 122

8.5.3 LoadingsPLS2, 124

8.5.4 WLoadingsPLS2, 125

8.5.5 QLoadingsPLS2, 126

8.6 Additional Functions, 127

8.6.1 MIdent, 127

8.6.2 MIdentD2, 127

8.6.3 MCutRows, 129

8.6.4 MTrace, 129

Conclusion, 130

PART IIICHEMOMETRICS 131

9 Principal Component Analysis (PCA) 133

9.1 The Basics, 133

9.1.1 Data, 133

9.1.2 Intuitive Approach, 134

9.1.3 Dimensionality Reduction, 136

9.2 Principal Component Analysis, 136

9.2.1 Formal Specifications, 136

9.2.2 Algorithm, 137

9.2.3 PCA and SVD, 137

9.2.4 Scores, 138

9.2.5 Loadings, 139

9.2.6 Data of Special Kind, 140

9.2.7 Errors, 140

9.2.8 Validation, 143

9.2.9 Decomposition "Quality", 143

9.2.10 Number of Principal Components, 144

9.2.11 The Ambiguity of PCA, 145

9.2.12 Data Preprocessing, 146

9.2.13 Leverage and Deviation, 146

9.3 People and Countries, 146

9.3.1 Example, 146

9.3.2 Data, 147

9.3.3 Data Exploration, 147

9.3.4 Data Pretreatment, 148

9.3.5 Scores and Loadings Calculation, 149

9.3.6 Scores Plots, 151

9.3.7 Loadings Plot, 152

9.3.8 Analysis of Residuals, 153

Conclusion, 153

10 Calibration 156

10.1 The Basics, 156

10.1.1 Problem Statement, 156

10.1.2 Linear and Nonlinear Calibration, 157

10.1.3 Calibration and Validation, 158

10.1.4 Calibration "Quality", 160

10.1.5 Uncertainty, Precision, and Accuracy, 162

10.1.6 Underfitting and Overfitting, 163

10.1.7 Multicollinearity, 164

10.1.8 Data Preprocessing, 166

10.2 Simulated Data, 166

10.2.1 The Principle of Linearity, 166

10.2.2 "Pure" Spectra, 166

10.2.3 "Standard" Samples, 166

10.2.4 X Data Creation, 167

10.2.5 Data Centering, 168

10.2.6 Data Overview, 168

10.3 Classic Calibration, 169

10.3.1 Univariate (Single Channel) Calibration, 169

10.3.2 The Vierordt Method, 172

10.3.3 Indirect Calibration, 174

10.4 Inverse Calibration, 176

10.4.1 Multiple Linear Calibration, 177

10.4.2 Stepwise Calibration, 178

10.5 Latent Variables Calibration, 180

10.5.1 Projection Methods, 180

10.5.2 Latent Variables Regression, 184

10.5.3 Implementation of Latent Variable Calibration, 185

10.5.4 Principal Component Regression (PCR), 186

10.5.5 Projection on the Latent Structures-1 (PLS1), 188

10.5.6 Projection on the Latent Structures-2 (PLS2), 191

10.6 Methods Comparison, 193

Conclusion, 197

11 Classification 198

11.1 The Basics, 198

11.1.1 Problem Statement, 198

11.1.2 Types of Classes, 199

11.1.3 Hypothesis Testing, 199

11.1.4 Errors in Classification, 200

11.1.5 One-Class Classification, 200

11.1.6 Training and Validation, 201

11.1.7 Supervised and Unsupervised Training, 201

11.1.8 The Curse of Dimensionality, 201

11.1.9 Data Preprocessing, 201

11.2 Data, 202

11.2.1 Example, 202

11.2.2 Data Subsets, 203

11.2.3 Workbook [...], 204

11.2.4 Principal Component Analysis, 205

11.3 Supervised Classification, 205

11.3.1 Linear Discriminant Analysis (LDA), 205

11.3.2 Quadratic Discriminant Analysis (QDA), 210

11.3.3 PLS Discriminant Analysis (PLSDA), 214

11.3.4 SIMCA, 217

11.3.5 k-Nearest Neighbors (kNN), 223

11.4 Unsupervised Classification, 225

11.4.1 PCA Again (Revisited), 225

11.4.2 Clustering by K-Means, 225

Conclusion, 229

12 Multivariate Curve Resolution 230

12.1 The Basics, 230

12.1.1 Problem Statement, 230

12.1.2 Solution Ambiguity, 232

12.1.3 Solvability Conditions, 234

12.1.4 Two Types of...