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 language | English (US) |
|---|---|
| Pages (from-to) | 493-500 |
| Number of pages | 8 |
| Journal | Statistics and its Interface |
| Volume | 17 |
| Issue number | 3 |
| DOIs | |
| State | Published - 2024 |
| Externally published | Yes |
Keywords
- B-splines
- Jump regression
- Nonparametric regression
- Normalized fused Lasso
ASJC Scopus subject areas
- Statistics and Probability
- Applied Mathematics