Simultaneous change-point detection and curve estimation*

Zhaoying Lu, Ning Hao, Hao Helen Zhang

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

In this work, we focus on a nonparametric regression model that accounts for discontinuities. We propose a method called Simultaneous CHange-point detection And Curve Estimation (SCHACE) for effectively detecting jumps in a data sequence and accurately capturing nonlinear trends between these jumps in the mean curve. The SCHACE is a unified regularization framework that incorporates two statistical tools: the normalized fused Lasso for change-point detection and B-splines for curve estimation. Notably, this approach is a single-step method that does not require iteration and is straightforward to implement. We demonstrate the advantages of the SCHACE by simulated and real-world data examples.

Original languageEnglish (US)
Pages (from-to)493-500
Number of pages8
JournalStatistics and its Interface
Volume17
Issue number3
DOIs
StatePublished - 2024
Externally publishedYes

Keywords

  • B-splines
  • Jump regression
  • Nonparametric regression
  • Normalized fused Lasso

ASJC Scopus subject areas

  • Statistics and Probability
  • Applied Mathematics

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