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Results of change point analysis (Pettitt’s Test), where p ≤ 0.5 is significant.

Figshare2020-09-18 更新2026-04-28 收录

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Results of change point analysis (Pettitt’s Test), where p ≤ 0.5 is significant.

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2020-09-18

时间序列分析

变化点检测

We introduce a new approach for decoupling trends (drift) and changepoints (shifts) in time series. Our locally adaptive model-based approach for robustly decoupling combines Bayesian trend filtering

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Efficient Multiple Change Point Detection and Localization For High-Dimensional Quantile Regression with Heteroscedasticity

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变化点检测

Data heterogeneity is a challenging issue for modern statistical data analysis. There are different types of data heterogeneity in practice. In this article, we consider potential structural changes a

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Variable Selection Based Testing for Parameter Changes in Regression with Autoregressive Dependence

变化点检测

金融风险建模

We consider a regression model with autoregressive terms and propose significance tests for the detection of change points in this model. Our tests are applicable to both low- or moderate dimension an

Taylor & Francis Group2024-02-26 更新60

A Likelihood Ratio Approach to Sequential Change Point Detection for a General Class of Parameters

变化点检测

时间序列分析

In this article, we propose a new approach for sequential monitoring of a general class of parameters of a d -dimensional time series, which can be estimated by approximately linear functionals

DataCite Commons2021-09-29 更新80

A Likelihood Ratio Approach to Sequential Change Point Detection for a General Class of Parameters

时间序列分析

变化点检测

In this article, we propose a new approach for sequential monitoring of a general class of parameters of a d -dimensional time series, which can be estimated by approximately linear functionals

DataCite Commons2025-06-01 更新60

Results of change point analysis (Pettitt’s Test), where p ≤ 0.5 is significant.

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