Morphometrics with R

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Springer Science & Business Media, Dec 15, 2008 - Science - 317 pages
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This book aims to explain how to use R to perform morphometrics. Morpho- tric analysis is the study of shape and size variations and covariations and their covariations with other variables. Morphometrics is thus deeply rooted within stat- tical sciences. While most applications concern biology, morphometrics is becoming common tools used in archeological, palaeontological, geographical, or medicine disciplines. Since the recent formalizations of some of the ideas of predecessors, such as D’arcy Thompson, and thanks to the development of computer techno- gies and new ways for appraising shape changes and variation, morphometrics have undergone, and are still undergoing, a revolution. Most techniques dealing with s- tistical shape analysis have been developed in the last three decades, and the number of publications using morphometrics is increasing rapidly. However, the majority of these methods cannot be implemented in available software and therefore prosp- tive students often need to acquire detailed knowledge in informatics and statistics before applying them to their data. With acceleration in the accumulation of me- ods accompanying the emerging science of statistical shape analysis, it is becoming important to use tools that allow some autonomy. R easily helps ful?ll this need. Risalanguage andenvironment forstatisticalcomputingandgraphics. Although there is an increasing number of computer applications that perform morphometrics, using R has several advantages that confer to users considerable power and possible new horizons in a world that requires rapid adaptability.
 

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Contents

Introduction
1
12 Shapes and Configurations
3
13 An R Approach to Morphometrics
5
14 Starting with R
9
142 Objects
10
143 Functions
17
144 Operators
21
146 Loops
23
42 Superimposition Methods
138
421 Removing the Size Effect
139
422 Baseline Registration and Bookstein Coordinates
141
423 Procrustes Methods and Kendall Coordinates
148
424 The Kendall Shape Space and the Tangent Euclidean Shape Space
166
425 Resistantfit Superimposition
170
43 ThinPlate Splines
181
44 Form and Euclidean Distance Matrix Analysis
189

Problems
24
Acquiring and Manipulating Morphometric Data
25
212 Organizing Data
27
22 Data Acquisition with R
31
222 Entering Data by Hand
32
224 Reading and Converting Image Files
33
225 Graphical Visualization
35
226 Image Analysis and Morphometric Data Acquisition with R
41
23 Manipulating and Creating Data with R
48
231 Obtaining Distance from Coordinates of Points
49
232 Calculating an Angle from Two Interlandmark Vectors
50
233 Regularly Spaced Pseudolandmarks
51
234 Outline Smoothing
54
24 Saving and Converting Data
56
25 Missing Data
60
252 Estimating Missing Landmarks on Symmetrical Structures
61
26 Measurement Error
63
262 Protocols for Estimating Measurement Error
65
Problems
66
Traditional Statistics for Morphometrics
68
311 Visualizing and Testing the Distribution
70
312 When Data are Organization in Several Groups
72
32 Bivariate Analyses
80
322 Analyzing the Relationship Between two Distance Measurements Regression
81
323 Analyzing the Relationship Between Two Distance Measurements in Different Groups
84
324 A Short Excursion to Generalized Linear Models
89
325 Interspecific Measurements and Phylogenetic Data
92
326 Allometry and Isometry
95
A Problem of Definition
98
34 Multivariate Morphometrics
105
342 Principal Component Analysis
106
343 Analyzing Several Groups with Several Variables
111
344 Analyzing Relationships Between Different Sets of Variables
124
345 Comparing Covariation or Dissimilarity Patterns Between Two Groups
128
Problems
129
Modern Morphometrics Based on Configurations of Landmarks
133
45 Anglebased Approaches for the Study of Shape Variation
198
Problems
203
Statistical Analysis of Outlines
205
51 Open Outlines
206
512 Splines
207
513 Bezier Polynomials
209
52 Fourier Analysis
212
521 Fourier Analysis Applied to Radii Variation of Closed Outlines
213
522 Fourier Analysis applied to the Tangent Angle
217
523 Elliptic Fourier Analysis
221
53 Eigenshape Analysis and Other Methods
229
Problems
232
Statistical Analysis of Shape using Modern Morphometrics
233
611 Landmark Data
234
62 Discriminant and Multivariate Analysis of Variance
248
622 Procrustes Data
251
63 Clustering
254
64 Morphometrics and Phylogenies
257
65 Comparing Covariation Patterns
262
66 Analyzing Developmental Patterns with Modern Morphometrics
267
662 Developmental Stability
272
663 Developmental Integration
276
Problems
279
Going Further with R
280
72 Writing Functions and Implementing Methods
287
Contour Acquisition Revisited
289
73 Interfacing and Hybridizing R
293
Using ImageMagick to Display High Resolution Images
296
74 Conclusion
297
Problems
298
Functions Developed in this Text
299
Packages Used in this Text
301
References
303
Index
311
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