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Prediction Revisited: The Importance of Observation

Prediction Revisited: The Importance of Observation (Hardcover)

Mark P. Kritzman, David Turkington, Megan Czasonis (지은이)
Wiley
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Prediction Revisited: The Importance of Observation
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책 정보

· 제목 : Prediction Revisited: The Importance of Observation (Hardcover) 
· 분류 : 외국도서 > 경제경영 > 투자/증권 > 금융자산 관리
· ISBN : 9781119895589
· 쪽수 : 240쪽
· 출판일 : 2022-06-08

목차

Timeline of Innovations ix

Essential Concepts xi

Preface xv

1 Introduction 1

Relevance 2

Informativeness 3

Similarity 4

Roadmap 4

2 Observing Information 7

Observing Information Conceptually 7

Central Tendency 8

Spread 9

Information Theory 10

The Strong Pull of Normality 14

A Constant of Convenience 17

Key Takeaways 18

Observing Information Mathematically 20

Average 20

Spread 21

Information Distance 24

Observing Information Applied 26

Appendix 2.1: On the Inflection Point of the Normal Distribution 32

References 39

3 Co-occurrence 41

Co-occurrence Conceptually 41

Correlation as an Information-Weighted Average of Co-occurrence 46

Pairs of Pairs 49

Across Many Attributes 50

Key Takeaways 52

Co-occurrence Mathematically 54

The Covariance Matrix 58

Co-occurrence Applied 59

References 66

4 Relevance 67

Relevance Conceptually 67

Informativeness 68

Similarity 72

Relevance and Prediction 73

How Much Have You Regressed? 74

Partial Sample Regression 76

Asymmetry 80

Sensitivity 86

Memory and Bias 87

Key Takeaways 88

Relevance Mathematically 90

Prediction 95

Equivalence to Linear Regression 97

Partial Sample Regression 100

Asymmetry 102

Relevance Applied 107

Appendix 4.1: Predicting Binary Outcomes 114

Predicting Binary Outcomes Conceptually 114

Predicting Binary Outcomes Mathematically 116

References 121

5 Fit 123

Fit Conceptually 123

Failing Gracefully 125

Why Fit Varies 126

Avoiding Bias 129

Precision 130

Focus 133

Key Takeaways 134

Fit Mathematically 136

Components of Fit 138

Precision 139

Fit Applied 143

6 Reliability 149

Reliability Conceptually 149

Key Takeaways 153

Reliability Mathematically 155

Reliability Applied 163

References 168

7 Toward Complexity 169

Toward Complexity Conceptually 169

Learning by Example 170

Expanding on Relevance 171

Key Takeaways 175

Toward Complexity Mathematically 177

Complexity Applied 183

References 183

8 Foundations of Relevance 185

Observations and Relevance: A Brief Review of the Main Insights 186

Spread 187

Co-occurrence 187

Relevance 188

Asymmetry 188

Fit and Reliability 189

Partial Sample Regression and Machine Learning Algorithms 189

Abraham de Moivre (1667–1754) 190

Pierre-Simon Laplace (1749–1827) 192

Carl Friedrich Gauss (1777–1853) 193

Francis Galton (1822–1911) 195

Karl Pearson (1857–1936) 197

Ronald Fisher (1890–1962) 199

Prasanta Chandra Mahalanobis (1893–1972) 200

Claude Shannon (1916–2001) 202

References 206

Concluding Thoughts 209

Perspective 209

Insights 210

Prescriptions 210

Index 211

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