Julien Claude
（2008年8月刊行，Springer-Verlag［Series: Use R!］, Berlin, ISBN:9780387777894 [pbk] → 版元ページ）
意外に早く現物が届いた．
【目次】
Preface vii
Contributors xi
Abbreviations and Notations xiii1 Introduction 1
1.1 Morphometrics Today 1
1.2 Shapes and Configurations 3
1.3 An R Approach to Morphometrics 5
1.4 Starting with R 9
1.4.1 Expression, Assignment and Other Basics 9
1.4.2 Objects 10
1.4.3 Functions 17
1.4.4 Operators 21
1.4.5 Generating Data 21
1.4.6 Loops 23
Problems 242 Acquiring and Manipulating Morphometric Data 25
2.1 Collecting and Organizing Morphometric Data 25
2.1.1 Collecting Data 25
2.1.2 Organizing Data 27
2.2 Data Acquisition with R 31
2.2.1 Loading and Reading R Datafiles 31
2.2.2 Entering Data by Hand 32
2.2.3 Reading Text Files 32
2.2.4 Reading and Converting Image Files 33
2.2.5 Graphical Visualization 35
2.2.6 Image Analysis and Morphometric Data Acquisition with R 41
2.3 Manipulating and Creating Data with R 48
2.3.1 Obtaining Distance from Coordinates of Points 49
2.3.2 Calculating an Angle from Two Interlandmark Vectors 50
2.3.3 Regularly Spaced Pseudolandmarks 51
2.3.4 Outline Smoothing 54
2.4 Saving and Converting Data 56
2.5 Missing Data 60
2.5.1 Estimating Missing Measurements by Multiple Regression 60
2.5.2 Estimating Missing Landmarks on Symmetrical Structures 61
2.6 Measurement Error 63
2.6.1 Sources of Measurement Error 63
2.6.2 Protocols for Estimating Measurement Error 65
Problems 663 Traditional Statistics for Morphometrics 69
3.1 Univariate Analyses 69
3.1.1 Visualizing and Testing the Distribution 70
3.1.2 When Data are Organized in Several Groups 72
3.2 Bivariate Analyses 80
3.2.1 Graphics 80
3.2.2 Analyzing the Relationship Between two Distance Measurements 81
3.2.3 Analyzing the Relationship Between Two Distance Measurements in Different Groups 84
3.2.4 A Short Excursion to Generalized Linear Models 89
3.2.5 Interspecific Measurements and Phylogenetic Data 92
3.2.6 Allometry and Isometry 95
3.3 Size: A Problem of Definition 98
3.4 Multivariate Morphometrics 105
3.4.1 Visualization of More than Two Distance Measurements 105
3.4.2 Principal Component Analysis 106
3.4.3 Analyzing Several Groups with Several Variables 111
3.4.4 Analyzing Relationships Between Different Sets of Variables 124
3.4.5 Comparing Covariation or Dissimilarity Patterns Between Two Groups 128
Problems 1294 Modern Morphometrics Based on Configurations of Landmarks 133
4.1 The Truss Network Approach of Strauss and Bookstein 133
4.2 Superimposition Methods 138
4.2.1 Removing the Size Effect 139
4.2.2 Baseline Registration and Bookstein Coordinates 141
4.2.3 Procrustes Methods and Kendall Coordinates 148
4.2.4 The Kendall Shape Space and the Tangent Euclidean Shape Space 166
4.2.5 Resistant-fit Superimposition 170
4.3 Thin-Plate Splines 181
4.4 Form and Euclidean Distance Matrix Analysis 189
4.5 Angle-based Approaches for the Study of Shape Variation 198
Problems 2035 Statistical Analysis of Outlines 205
5.1 Open Outlines 206
5.1.1 Polynomial Curves 206
5.1.2 Splines 207
5.1.3 Bezier Polynomials 209
5.2 Fourier Analysis 212
5.2.1 Fourier Analysis Applied to Radii Variation of Closed Outlines 213
5.2.2 Fourier Analysis applied to the Tangent Angle 217
5.2.3 Elliptic Fourier Analysis 221
5.3 Eigenshape Analysis and Other Methods 229
Problems 2326 Statistical Analysis of Shape using Modern Morphometrics 233
6.1 Explorative Analyses of the Shape Space 233
6.1.1 Landmark Data 234
6.1.2 Outlines 244
6.2 Discriminant and Multivariate Analysis of Variance 248
6.2.1 Outlines 248
6.2.2 Procrustes Data 251
6.3 Clustering 254
6.4 Morphometrics and Phylogenies 257
6.5 Comparing Covariation Patterns 262
6.6 Analyzing Developmental Patterns with Modern Morphometrics 267
6.6.1 Allometry 267
6.6.2 Developmental Stability 272
6.6.3 Developmental Integration 276
Problems 2797 Going Further with R 281
7.1 Simulations 281
7.2 Writing Functions and Implementing Methods 287
7.2.1 Generalities and Strategies 287
7.2.2 A Worked Example in R+C Programming: Contour Acquisition Revisited 289
7.3 Interfacing and Hybridizing R 293
7.3.1 Example 1: Creating an Animation with R and ImageMagick 293
7.3.2 Example 2: Using ImageMagick to Display High Resolution Images 296
7.4 Conclusion 297
Problems 298
Appendix A: Functions Developed in this Text 299
Appendix B: Packages Used in this Text 301
References 303
Index 311
