August 1, 2025Statistical Analysis and Data Mining The ASA Data Science Journal

Model Average Estimation of Parameters in Linear Model With Multiple Change Points

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Authors

HSHang SuBroad Institute MHMinjie Huang ZXZhiming XiaHuaihua University

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Overview

This paper develops a model averaging method that improves parameter estimation in segmented linear regression with multiple change points, highlighting its effectiveness.

Key Points

The proposed MMA method effectively reduces squared error in estimating parameters with change points, improving accuracy.
Key evidence shows that the MMA estimator is root-n consistent and asymptotically optimal under model deviations.
Observation using simulation studies demonstrates superior performance compared to traditional estimation methods.
The methodology is promising for applications involving structural breaks, suggesting practical relevance in various contexts.

Cite This Study

Su et al. (2025) studied this question.

synapsesocial.com/papers/68af61fdad7bf08b1eae2acc https://doi.org/10.1002/sam.70043

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August 1, 2025Statistical Analysis and Data Mining The ASA Data Science Journal

Model Average Estimation of Parameters in Linear Model With Multiple Change Points

View Full Paper

Ask AI

Bookmark

Authors

HSHang SuBroad Institute MHMinjie Huang ZXZhiming XiaHuaihua University

Discussion

Member takes

Overview

This paper develops a model averaging method that improves parameter estimation in segmented linear regression with multiple change points, highlighting its effectiveness.

Key Points

The proposed MMA method effectively reduces squared error in estimating parameters with change points, improving accuracy.
Key evidence shows that the MMA estimator is root-n consistent and asymptotically optimal under model deviations.
Observation using simulation studies demonstrates superior performance compared to traditional estimation methods.
The methodology is promising for applications involving structural breaks, suggesting practical relevance in various contexts.

Cite This Study

Su et al. (2025) studied this question.

synapsesocial.com/papers/68af61fdad7bf08b1eae2acc https://doi.org/10.1002/sam.70043

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