Energy statistics are functions of distances between statistical observations in metric spaces. The authors hope this book will spark the interest of most statisticians who so far have not explored E-statistics and would like to apply these new methods using R.

Part 1: The Energy of Data 1. Introduction 2. Preliminaries 3. Energy Distance 4. Introduction to Energy Inference 5. Goodness-of-Fit 6. Testing Multivariate Normality 7. Eigenvalues for One-Sample E-Statistics 8. Generalized Goodness-of-Fit 9. Multi-sample Energy Statistics 10. Energy in Metric Spaces and Other Distances Part 2: Distance Correlation and Dependence 11. On Correlation and Other Measures of Association 12. Distance Correlation 13. Testing Independence 14. Applications and Extensions 15. Brownian Distance Covariance 16. U-statistics and Unbiased dCov2 17. Partial Distance Correlation 18. The Numerical Value of dCor 19. The dCor t-test of Independence in High Dimension 20. Computational Algorithms 21. Time Series and Distance Correlation 22. Axioms of Dependence Measures 23. Earth Mover's Correlation 24. Appendix A: Historical Background 25. Appendix B: Prehistory