论文标题
在R中快速核平滑，并应用投影追求
Fast Kernel Smoothing in R with Applications to Projection Pursuit
论文作者
论文摘要
本文介绍了R套件FKSUM，该软件包提供了对单变量内核Smoothers的快速评估。主要内核计算在C ++中实现，并包裹在简单，直观和通用的R函数中。快速内核计算基于涉及顺序统计数据的递归表达式，该表达式可以在对数线性时间中所有样本点上的所有样本点进行精确评估。除了通用内核平滑功能外，该软件包还提供了流行内核型估计器的目的和现成的实现。除了这些基本的平滑问题之外，本文重点介绍了投影指数基于投影密度功能的内核型估计值的投影追求问题。
This paper introduces the R package FKSUM, which offers fast and exact evaluation of univariate kernel smoothers. The main kernel computations are implemented in C++, and are wrapped in simple, intuitive and versatile R functions. The fast kernel computations are based on recursive expressions involving the order statistics, which allows for exact evaluation of kernel smoothers at all sample points in log-linear time. In addition to general purpose kernel smoothing functions, the package offers purpose built and ready-to-use implementations of popular kernel-type estimators. On top of these basic smoothing problems, this paper focuses on projection pursuit problems in which the projection index is based on kernel-type estimators of functionals of the projected density.
