Divided Differences, Falling Factorials, and Discrete Splines: Another Look at Trend Filtering and Related Problems

R. Tibshirani
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引用次数: 13

Abstract

This paper serves as a postscript of sorts to Tibshirani (2014); Wang et al. (2014), who developed continuous-time formulations and properties of trend filtering, a discrete-time smoothing tool proposed (independently) by Steidl et al. (2006); Kim et al. (2009). The central object of study is the falling factorial basis, as it was called by Tibshirani (2014); Wang et al. (2014). Its span turns out to be a space of piecewise polynomials that has a classical place in spline theory, called discrete splines (Mangasarian and Schumaker, 1971, 1973; Schumaker, 2007). At the Tibshirani (2014); Wang et al. (2014), we were not fully aware of these connections. The current paper attempts to rectify this by making these connections explicit, reviewing (and making use of) some of the important existing work on discrete splines, and contributing several new perspectives and new results on discrete splines along the way.
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可分差、下降阶乘和离散样条:趋势过滤和相关问题的另一个视角
本文可作为Tibshirani(2014)的后记;Wang et al.(2014)开发了连续时间公式和趋势滤波的性质,趋势滤波是Steidl et al.(2006)(独立)提出的离散时间平滑工具;Kim等人(2009)。研究的中心对象是下降因子基础,因为它被称为Tibshirani (2014);Wang et al.(2014)。它的跨度是一个分段多项式的空间,在样条理论中有一个经典的位置,称为离散样条(Mangasarian和Schumaker, 1971,1973;舒梅克,2007)。在Tibshirani (2014);Wang et al.(2014),我们并没有完全意识到这些联系。当前的论文试图通过明确这些联系来纠正这一点,回顾(并利用)一些重要的现有离散样条的工作,并在此过程中对离散样条提供一些新的观点和新的结果。
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