Grouped Change-Points Detection and Estimation in Panel Data
The change-points in panel data can be obstacles for fitting models; thus, detecting change-points accurately before modeling is crucial. Extant methods often either assume that all panels share the common change-points or that grouped panels have the same unknown parameters. However, the problem of...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-03-01
|
| Series: | Mathematics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-7390/12/5/750 |
| _version_ | 1797264166276300800 |
|---|---|
| author | Haoran Lu Dianpeng Wang |
| author_facet | Haoran Lu Dianpeng Wang |
| author_sort | Haoran Lu |
| collection | DOAJ |
| description | The change-points in panel data can be obstacles for fitting models; thus, detecting change-points accurately before modeling is crucial. Extant methods often either assume that all panels share the common change-points or that grouped panels have the same unknown parameters. However, the problem of different change-points and model parameters between panels has not been solved. To deal with this problem, a novel approach is proposed here to simultaneously detect and estimate the grouped change-points precisely by employing an iterative algorithm and the penalty cost function. Some numerical experiments and case studies are utilized to demonstrate the superior performance of the proposed method in grouping the panels, and estimating the number and positions of change-points. |
| first_indexed | 2024-04-25T00:24:35Z |
| format | Article |
| id | doaj.art-93882b388db145c3b3d7c1b49b62916e |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-04-25T00:24:35Z |
| publishDate | 2024-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-93882b388db145c3b3d7c1b49b62916e2024-03-12T16:50:12ZengMDPI AGMathematics2227-73902024-03-0112575010.3390/math12050750Grouped Change-Points Detection and Estimation in Panel DataHaoran Lu0Dianpeng Wang1The School of Mathematics and Statistics, Beijing Institute of Technology, Beijing 100081, ChinaThe School of Mathematics and Statistics, Beijing Institute of Technology, Beijing 100081, ChinaThe change-points in panel data can be obstacles for fitting models; thus, detecting change-points accurately before modeling is crucial. Extant methods often either assume that all panels share the common change-points or that grouped panels have the same unknown parameters. However, the problem of different change-points and model parameters between panels has not been solved. To deal with this problem, a novel approach is proposed here to simultaneously detect and estimate the grouped change-points precisely by employing an iterative algorithm and the penalty cost function. Some numerical experiments and case studies are utilized to demonstrate the superior performance of the proposed method in grouping the panels, and estimating the number and positions of change-points.https://www.mdpi.com/2227-7390/12/5/750grouped change-pointinteger programmingpenalty cost functionpanel data |
| spellingShingle | Haoran Lu Dianpeng Wang Grouped Change-Points Detection and Estimation in Panel Data Mathematics grouped change-point integer programming penalty cost function panel data |
| title | Grouped Change-Points Detection and Estimation in Panel Data |
| title_full | Grouped Change-Points Detection and Estimation in Panel Data |
| title_fullStr | Grouped Change-Points Detection and Estimation in Panel Data |
| title_full_unstemmed | Grouped Change-Points Detection and Estimation in Panel Data |
| title_short | Grouped Change-Points Detection and Estimation in Panel Data |
| title_sort | grouped change points detection and estimation in panel data |
| topic | grouped change-point integer programming penalty cost function panel data |
| url | https://www.mdpi.com/2227-7390/12/5/750 |
| work_keys_str_mv | AT haoranlu groupedchangepointsdetectionandestimationinpaneldata AT dianpengwang groupedchangepointsdetectionandestimationinpaneldata |