版块导航: 正在加载中...

登录注册

应《网络安全法》要求，自2017年10月1日起，未进行实名认证将不得使用互联网跟帖服务。为保障您的帐号能够正常使用，请尽快对帐号进行手机号验证，感谢您的理解与支持！

24小时热门版块排行榜

返回列表

【奖励】本帖被评价131次，作者lukecana增加金币 104.2 个

lukecana

至尊木虫 (著名写手)

ACI: 1
应助: 18 (小学生)
金币: 17916.8
帖子: 2279
在线: 498.3小时
虫号: 667753

[资源] 2014新书：excel 化学计量学（英文）

Chemometrics in Excel
by Alexey L. Pomerantsev
Hardcover: 336 pages
Publisher: Wiley; 1 edition (May 19, 2014)
Language: English
ISBN-10: 1118605357
ISBN-13: 978-1118605356
Reviews
Topics in the book include an introduction to chemometrics. It also details the basics of chemometrics, topics in Chemometrics include Principal component analysis, Calibration, Classification, and Multivariate Curve Resolution. Supplements such as an Extension of the Chemometrics AddIn, Kinetic modeling of spectral data, and a MatLab Beginners Guide are also included.
Table of Contents
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 Iris.xls, 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 Data, 235

12.1.5 Known Spectrum or Profile, 236

12.1.6 Principal Component Analysis (PCA), 236

12.1.7 PCA and MCR, 237

12.2 Simulated Data, 237

12.2.1 Example, 237

12.2.2 Data, 238

12.2.3 PCA, 238

12.2.4 The HELP Plot, 240

12.3 Factor Analysis, 241

12.3.1 Procrustes Analysis, 241

12.3.2 Evolving Factor Analysis (EFA), 244

12.3.3 Windows Factor Analysis (WFA), 246

12.4 Iterative Methods, 249

12.4.1 Iterative Target Transform Factor Analysis (ITTFA), 249

12.4.2 Alternating Least Squares (ALS), 250

Conclusion, 252

PART IV SUPPLEMENTS 255

13 Extension Of Chemometrics Add-In 257

13.1 Using Virtual Arrays, 257

13.1.1 Simulated Data, 257

13.1.2 Virtual Array, 259

13.1.3 Data Preprocessing, 259

13.1.4 Decomposition, 260

13.1.5 Residuals Calculation, 260

13.1.6 Eigenvalues Calculation, 262

13.1.7 Orthogonal Distances Calculation, 263

13.1.8 Leverages Calculation, 264

13.2 Using VBA Programming, 265

13.2.1 VBA Advantages, 265

13.2.2 Virtualization of Real Arrays, 265

13.2.3 Data Preprocessing, 266

13.2.4 Residuals Calculation, 267

13.2.5 Eigenvalues Calculation, 268

13.2.6 Orthogonal Distances Calculation, 269

13.2.7 Leverages Calculation, 270

Conclusion, 271

14 Kinetic Modeling of Spectral Data 272

14.1 The “Grey” Modeling Method, 272

14.1.1 Problem Statement, 272

14.1.2 Example, 274

14.1.3 Data, 274

14.1.4 Soft Method of Alternating Least Squares (Soft-ALS), 275

14.1.5 Hard Method of Alternating Least Squares (Hard-ALS), 277

14.1.6 Using Solver Add-In, 279

Conclusions, 282

15 MATLAB: Beginner’s Guide 283

15.1 The Basics, 283

15.1.1 Workspace, 283

15.1.2 Basic Calculations, 285

15.1.3 Echo, 285

15.1.4 Workspace Saving: MAT-Files, 286

15.1.5 Diary, 286

15.1.6 Help, 287

15.2 Matrices, 287

15.2.1 Scalars, Vectors, and Matrices, 287

15.2.2 Accessing Matrix Elements, 289

15.2.3 Basic Matrix Operations, 289

15.2.4 Special Matrices, 290

15.2.5 Matrix Calculations, 292

15.3 Integrating Excel and MATLAB, 294

15.3.1 Configuring Excel, 294

15.3.2 Data Exchange, 294

15.4 Programming, 295

15.4.1 M-Files, 295

15.4.2 Script File, 296

15.4.3 Function File, 297

15.4.4 Plotting, 298

15.4.5 Plot Printing, 300

15.5 Sample Programs, 301

15.5.1 Centering and Scaling, 301

15.5.2 SVD/PCA, 301

15.5.3 PCA/NIPALS, 302

15.5.4 PLS1, 303

15.5.5 PLS2, 304

Conclusion, 306

Afterword. The Fourth Paradigm 307
-
-

--

chemexel.jpg

回复此楼

» 本帖附件资源列表

欢迎监督和反馈：小木虫仅提供交流平台，不对该内容负责。
本内容由用户自主发布，如果其内容涉及到知识产权问题，其责任在于用户本人，如对版权有异议，请联系邮箱：xiaomuchong@tal.com
附件 1 : Chemometrics_in_Excel.rar

2014-08-22 22:26:48, 5.66 M

» 收录本帖的淘帖专辑推荐

专业书籍（外文版）WM	化学专业电子资源	学习资料（理工类）	Allen的英文原版+百科
科研电子书共享	【计算机应用化学】	化工	软件及教程
技术	chemometrics	仪器分析	标准
信步闲庭	药物分析	books	科研软件资源
study

» 本帖已获得的红花（最新10朵）

jinyun12112330

» 猜你喜欢

» 本主题相关价值贴推荐，对您同样有帮助:

化学计量学 R^2 已经有10人回复

1楼 2014-08-22 22:26:53

已阅回复此楼关注TA 给TA发消息送TA红花 TA的回帖

zhaoyf2008

铜虫 (初入文坛)

应助: 0 (幼儿园)
金币: 125.8
帖子: 18
在线: 33.9小时
虫号: 2096581

★★★ 三星级,支持鼓励

thank you

回复此楼

10楼2014-08-23 16:16:42

已阅回复此楼关注TA 给TA发消息送TA红花 TA的回帖

简单回复

MJF6282楼

2014-08-22 23:00 回复

五星好评顶一下，感谢分享！

wallan873楼

2014-08-23 00:20 回复

五星好评顶一下，感谢分享！

lam08990054楼

2014-08-23 00:42 回复

五星好评顶一下，感谢分享！

lp7775楼

2014-08-23 08:07 回复

三星好评顶一下，感谢分享！

蛛捕鸟6楼

2014-08-23 08:29 回复

五星好评顶一下，感谢分享！

startover_t7楼

2014-08-23 14:11 回复

顶一下，谢谢分享！

lwg38楼

2014-08-23 14:54 回复

五星好评顶一下，感谢分享！

w_wwb9楼

2014-08-23 15:40 回复

五星好评顶一下，感谢分享！

qwwz-zry11楼

2014-08-23 16:21 回复

五星好评顶一下，感谢分享！

lcf200612楼

2014-08-23 18:13 回复

五星好评顶一下，感谢分享！

独叶一支枪13楼

2014-08-23 18:16 回复

五星好评顶一下，感谢分享！

xiaolove200014楼

2014-08-23 22:00 回复

五星好评顶一下，感谢分享！

wuyq650215楼

2014-08-23 22:53 回复

五星好评顶一下 [ 发自小木虫客户端 ]

gaojianwqjk16楼

2014-08-23 23:45 回复

五星好评顶一下，感谢分享！

everie17楼

2014-08-24 01:16 回复

五星好评

marchfeng18楼

2014-08-24 03:07 回复

五星好评顶一下，感谢分享！

wmnick19楼

2014-08-24 06:07 回复

五星好评顶一下，感谢分享！

qqchun20楼

2014-08-24 08:28 回复

五星好评顶一下，感谢分享！

kmjida21楼

2014-08-24 08:50 回复

顶一下，感谢分享！

ld037122楼

2014-08-24 10:36 回复

五星好评顶一下，感谢分享！

yuhua050223楼

2014-08-24 11:57 回复

五星好评感谢分享啦

hy28530637924楼

2014-08-24 12:18 回复

五星好评顶一下，感谢分享！

ppttmm25楼

2014-08-24 12:21 回复

五星好评顶一下，感谢分享！

tingy198626楼

2014-08-24 16:23 回复

五星好评顶一下，感谢分享！

wang36927楼

2014-08-24 16:30 回复

五星好评顶一下，感谢分享！

jj19739410128楼

2014-08-24 16:56 回复

五星好评顶一下，感谢分享！

muxinjin29楼

2014-08-24 18:15 回复

五星好评顶一下，感谢分享！

xuhu_1130楼

2014-08-24 19:23 回复

五星好评顶一下，感谢分享！

q29038331831楼

2014-08-24 20:23 回复

五星好评顶一下，感谢分享！

gretzky32楼

2014-08-24 22:23 回复

五星好评顶一下，感谢分享！

tswangan33楼

2014-08-24 22:43 回复

五星好评顶一下，感谢分享！

cq2005_hj34楼

2014-08-24 23:49 回复

五星好评顶一下，感谢分享！

1314168apple35楼

2014-08-25 12:50 回复

五星好评顶一下，感谢分享！

xp—fly36楼

2014-08-25 14:24 回复

五星好评顶一下，感谢分享！

liudr37楼

2014-08-25 14:41 回复

五星好评顶一下，感谢分享！

yyaomao93938楼

2014-08-25 17:25 回复

五星好评顶一下，感谢分享！

yaya21339楼

2014-08-25 20:26 回复

五星好评顶一下，感谢分享！

dashing40楼

2014-08-25 22:09 回复

五星好评顶一下，感谢分享！

liucfcuil41楼

2014-08-26 06:32 回复

五星好评

Quan.42楼

2014-08-26 06:54 回复

五星好评顶一下，感谢分享！

yonglin-6543楼

2014-08-26 09:02 回复

五星好评顶一下，感谢分享！

kldc344楼

2014-08-26 11:42 回复

五星好评顶一下，感谢分享！

redfish45楼

2014-08-26 11:47 回复

三星好评顶一下，感谢分享！

VDFEPI46楼

2014-08-26 16:33 回复

五星好评顶一下，感谢分享！

yimj47楼

2014-08-26 16:47 回复

五星好评顶一下，感谢分享！

ypp518148楼

2014-08-26 22:38 回复

五星好评顶一下，感谢分享！

wu_gang100049楼

2014-08-27 09:33 回复

五星好评顶一下，感谢分享！

biosensors50楼

2014-08-27 11:04 回复

三星好评顶一下，感谢分享！

相关版块跳转我要订阅楼主 lukecana 的主题更新

返回列表

☆ 无星级 ★ 一星级 ★★★ 三星级 ★★★★★ 五星级

普通表情龙兔虎猫高级回复 (可上传附件)