Limit theorems for the union-intersection test

DOI10.1016/0378-3758(94)00049-2zbMath0816.62020OpenAlexW2017396014MaRDI QIDQ1347118

Lajos Horváth, Qui-Man Shao

Publication date: 2 July 1995

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0378-3758(94)00049-2

zbMATH Keywords

consistencyunion-intersection principleextreme-value distributionstrong approximation of partial sums

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Strong limit theorems (60F15) Asymptotic properties of parametric tests (62F05)

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Cites Work

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• The maximum likelihood method for testing changes in the parameters of normal observations
• A limit theorem for the maximum of normalized sums of independent random variables
• Almost sure invariance principles for weakly dependent vector-valued random variables
• Distribution function inequalities for martingales
• Limit theorems for change in linear regression
• Tests of the Hypothesis that a Linear Regression System Obeys Two Separate Regimes
• A u-i approach to retrospective testing for shifting parameters in a linear model
• Rank tests for changepoint problems
• Limit theorems for sums of weakly dependent Banach space valued random variables
• A New Approach to Estimating Switching Regressions
• The Estimation of the Parameters of a Linear Regression System Obeying Two Separate Regimes