  It has recently been shown that an unbinned distance-based statistic, the
energy, can be used to construct an extremely powerful nonparametric
multivariate two sample goodness-of-fit test. An extension to this method that
makes it possible to perform nonparametric regression using multiple
multivariate data sets is presented in this paper. The technique, which is
based on the concept of minimizing the energy of the system, permits
determination of parameters of interest without the need for parametric
expressions of the parent distributions of the data sets. The application and
performance of this new method is discussed in the context of some simple
example analyses.
