基于最小能量概念的非参数回归
Nonparametric Regression using the Concept of Minimum Energy
摘要：
最近的研究表明，一个未分组的基于距离的统计量，能量，可以用来构建一个非常强大的非参数多变量两样本拟合优度检验。本文提出了一种扩展这种方法，使它能够使用多个多元数据集进行非参数回归。该技术，这是基于系统的能量最小化的概念，允许确定感兴趣的参数，而不需要的数据集的父分布的参数表达式。这种新方法的应用和性能进行了讨论的背景下，一些简单的例子分析。
英文摘要：
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.
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