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Approximations to the p-values of tests for a change-point under non-standard conditions
Author(s)
Date Issued
2016
Date Available
2016-08-03T01:00:11Z
Abstract
Three test statistics for a change-point in a linear model, variants of those considered by Andrews and Ploberger [Optimal tests when a nusiance parameter is present only under the alternative. Econometrica. 1994;62:1383–1414]: the sup-likelihood ratio (LR) statistic; a weighted average of the exponential of LR-statistics and a weighted average of LR-statistics, are studied. Critical values for the statistics with time trend regressors, obtained via simulation, are found to vary considerably, depending on conditions on the error terms. The performance of the bootstrap in approximating p-values of the distributions is assessed in a simulation study. A sample approximation to asymptotic analytical expressions extending those of Kim and Siegmund [The likelihood ratio test for a change-point in simple linear regression. Biometrika. 1989;76:409–423] in the case of the sup-LR test is also assessed. The approximations and bootstrap are applied to the Quandt data [The estimation of a parameter of a linear regression system obeying two separate regimes. J Amer Statist Assoc. 1958;53:873–880] and real data concerning a change-point in oxygen uptake during incremental exercise testing and the bootstrap gives reasonable results.
Sponsorship
Science Foundation Ireland
Type of Material
Journal Article
Publisher
Taylor and Francis
Journal
Journal of Statistical Computation and Simulation
Volume
86
Issue
7
Start Page
1430
End Page
1449
Copyright (Published Version)
2015 Taylor and Francis
Language
English
Status of Item
Peer reviewed
This item is made available under a Creative Commons License
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