Trend filtering by adaptive piecewise polynomials

被引：0

作者：

Jeong, Juyoung ^{[1
]}

Jung, Yoon Mo ^{[2
]}

Kim, Soo Hyun ^{[1
]}

Yun, Sangwoon ^{[3
]}

机构：

[1] Sungkyunkwan Univ, Appl Algebra & Optimizat Res Ctr, Seoul 16419, South Korea

[2] Sungkyunkwan Univ, Dept Math, Suwon 16419, South Korea

[3] Sungkyunkwan Univ, Dept Math Educ, Seoul 03063, South Korea

来源：

COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION | 2023年 / 116卷

基金：

新加坡国家研究基金会;

关键词：

Trend filtering; Piecewise polynomial regression; Nonlinear regression; Breakpoint merging;

D O I：

10.1016/j.cnsns.2022.106866

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

Trend filtering is a regression problem to estimate underlying trends in time series data. It is necessary to investigate data in various disciplines. We propose a trend filtering method by adaptive piecewise polynomials. More specifically, we adjust the location and the number of breakpoints or knots to obtain a better fitting to given data. The numerical results on synthetic and real data sets show that it captures distinct features such as abrupt changes or kinks and provides a simplified form and brief summary of given data.(c) 2022 Elsevier B.V. All rights reserved.

引用

页数：13

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