Fred L. Bookstein
（2014年刊行，Cambridge University Press, New York, xxviii + 535 pp. + 4 color plates, ISBN:9781107024151 [hbk] / ISBN:9781107722828 [eBook] → 版元ページ）
数値解析と統計的推論の世界を C. S. Peirce の「Abduction」と Edward O. Wilson の「Consilience」をキーワードに展開する大著．600ページ近くある．幾何学的形態測定学も統合されている．最初から最後まで読まないと！
【目次】
Analytical Tables of Contents xi
Preface xix
Epigraphs xxvii
Part I. The Basic Structure of a Numerical Inference 1
1. Getting Started 3
1.1 Our Central Problem: What Is a Good Numerical Inference? 3
1.2 The Sinking of the Scorpion 5
1.3 Prospectus 52. Consilience as a Rhetorical Strategy 17
2.1 Continental Drift 18
2.2 E. O. Wilson’s View of Consilience 28
2.3 Some Earlier Critiques 37
2.4 The Issue of Heterogeneity 42
2.5 The Graphics of Consilience 51
2.A Mathematical or Physics? Consilience and Celestrial Mechanics 58
2.B Historical Note: From Weiss through Kuhn to This Book 703. Abduction and Strong Inference 73
3.1 Example: Global Warming Is Anthropogenic 74
3.2 That Hypothesis Wins That Is the Only One That Fits the Data 85
3.3 Numerical Inferences Are the Natural Home of Abductive Reasoning 94
3.4 Strong Inference 100
3.5 Summary of Part I 105
3.A Appendix: Update on the Rhetoric of Climate Change 106
Part II. A Sampler of Strategies 113
4. The Undergraduate Course 115
E4.1 John Snow on the Origin of Cholera 117
L4.1 The Logic and Algebra of Least Squares 129
E4.2 Millikan and the Photoeclectic Effect 143
L4.2 Galton’s Machine 150
E4.3 Jean Perrin and the Reality of Atoms 175
L4.3 Likelihood-Based Statistical Inference 188
E4.4 Ulcers Are Infectious 201
L4.4 Avoiding Pathologies and Pitfalls 206
E4.5 Consilience and the Double Helix 214
L4.5 From Correlation to Multiple Regression 220
E4.6 On Passive Smoking 253
L4.6 Plausible Rival Hypotheses 263
E4.7 Milgram’s Obedience Experiment 266
E4.8 Death of the Dinosaurs 280
Interim Concluding Remark 284
Part III. Numerical Inference for General Systems 289
5. Abduction and Consilience in More Complicated Systems 291
5.1 Analysis of Patterns in the Presence of Complexity 291
5.2 Abduction and Consilience in General Systems 301
5.3 Information and Information-Based Statistics 331
5.4 A Concluding Comment 3446. The Singular-Value Decomposition: A Family of Pattern Engines for Organized Systems 346
6.1 The Hyperbolic Paraboloid 346
6.2 The Singular-Value Decompositions 349
6.3 Principal Components Analysis 357
6.4 Partial Least Squares and Related Methods for Associations Among Multiple Measurement Domains 366
6.5 Another Tableau: Dissimilarity as Primary Data 381
6.6 Concluding Comment 3997. Morphometrics, and Other Examples 402
7.1 Description by Landmark Configulations 406
7.2 Procrustes Shape Distance 410
7.3 Procrustes Shape Coordinates and Their Subspaces 412
7.4 Procrustes Form Distance 419
7.5 The Thin-Plate Spline in 2D and 3D 421
7.6 Semilandmarks: Representation and Information Content of Curving Form 426
7.7 Putting Everything Together: Examples 437
7.8 Other Examples 461
Part IV. What Is to Be Done? 479
8. Retrospect and Prospect 481
8.1 Abduction, Consilience, and Psychosocial Structure of Science 481
8.2 Implications for Inference Across the Sciences 491
8.3 What, Then, IS to Be Done? 493
References 501
Index 519
