Energy distance is a statistical distance between the distributions of
random vectors, which characterizes equality of distributions. The name
energy derives from Newton's gravitational potential energy, and there
is an elegant relation to the notion of potential energy between
statistical observations. 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.
The Energy of Data and Distance Correlation is intended for teachers
and students looking for dedicated material on energy statistics, but
can serve as a supplement to a wide range of courses and areas, such as
Monte Carlo methods, U-statistics or V-statistics, measures of
multivariate dependence, goodness-of-fit tests, nonparametric methods
and distance based methods.
-E-statistics provides powerful methods to deal with problems in
multivariate inference and analysis.
-Methods are implemented in R, and readers can immediately apply them
using the freely available energy package for R.
-The proposed book will provide an overview of the existing
state-of-the-art in development of energy statistics and an overview of
applications.
-Background and literature review is valuable for anyone considering
further research or application in energy statistics.
