The limit distributions of likelihood ratio and cumulative sum tests for a change in a binomial probability
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Publication:1263897
DOI10.1016/0047-259X(89)90057-2zbMath0688.62018OpenAlexW2073166362MaRDI QIDQ1263897
Publication date: 1989
Published in: Journal of Multivariate Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/0047-259x(89)90057-2
likelihood ratio testBrownian bridgeextreme value distributionGumbel distributionchange pointdouble exponential distributionnormalizing sequencescentralizingcumulative sums tests
Asymptotic properties of parametric estimators (62F12) Asymptotic distribution theory in statistics (62E20) Central limit and other weak theorems (60F05)
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Cites Work
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- A Non-Parametric Approach to the Change-Point Problem
- A limit theorem for the maximum of normalized sums of independent random variables
- The power of likelihood ratio and cumulative sum tests for a change in a binomial probability
- An approximation of partial sums of independent RV's, and the sample DF. II
- An approximation of partial sums of independent RV'-s, and the sample DF. I
- A Bayesian approach to inference about a change-point in a sequence of random variables
- Testing a Sequence of Observations for a Shift in Location
- Inference about the change-point in a sequence of binomial variables
- Estimating the Current Mean of a Normal Distribution which is Subjected to Changes in Time