Detecting a change in regression: First-order optimality
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Publication:1583892
DOI10.1214/aos/1017939243zbMath0963.62077OpenAlexW1986537892MaRDI QIDQ1583892
Moshe Pollak, Abba M. Krieger, Benjamin Yakir
Publication date: 3 July 2001
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1214/aos/1017939243
Applications of statistics in engineering and industry; control charts (62P30) Sequential statistical analysis (62L10) Optimal stopping in statistics (62L15)
Related Items (16)
APPLIED REGRESSION ANALYSIS BIBLIOGRAPHY UPDATE 2000–2001 ⋮ Statistical Surveillance. Optimality and Methods ⋮ Jump estimation in inverse regression ⋮ Comparative performance analysis of the Cumulative Sum chart and the Shiryaev‐Roberts procedure for detecting changes in autocorrelated data ⋮ Is Average Run Length to False Alarm Always an Informative Criterion? ⋮ Sequential Change-Point Detection Procedures That are Nearly Optimal and Computationally Simple ⋮ Guaranteed maximum likelihood splitting tests of a linear regression model ⋮ Sequential change-point detection when unknown parameters are present in the pre-change distribution ⋮ Change point problems in the model of logistic regression ⋮ Guaranteed testing for epidemic changes of a linear regression model ⋮ Optimal sequential kernel detection for dependent processes ⋮ A power study ofk-linear-r-ahead recursive residuals test for change-point in finite sequences ⋮ Martingale Type Statistics Applied to Change Points Detection ⋮ Guaranteed Local Maximum Likelihood Detection of a Change Point in Nonparametric Logistic Regression ⋮ Random Walks with Drift – A Sequential Approach ⋮ Optimal Surveillance Based on Exponentially Weighted Moving Averages
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- A diffusion process and its applications to detecting a change in the drift of Brownian motion
- Asymptotically optimal ditiction of a change in a linear model
- Procedures for Reacting to a Change in Distribution
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