Statistics and Its Interface

Volume 17 (2024)

Number 3

Simultaneous change-point detection and curve estimation

Pages: 493 – 500

DOI: https://dx.doi.org/10.4310/23-SII807

Authors

Zhaoying Lu (The University of Arizona)

Ning Hao (The University of Arizona)

Hao Zhang (The University of Arizona)

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.

Keywords

B-splines, jump regression, nonparametric regression, normalized fused lasso

2010 Mathematics Subject Classification

Primary 62G08. Secondary 62J07.

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Received 25 December 2022

Accepted 16 July 2023

Published 19 July 2024