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PubMed · 10985235

Multiple-changepoint testing for an alternating segments model of a binary sequence.

A L Halpern
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Abstract

A binary sequence may give the appearance of being composed of alternating segments with relatively high and relatively low probability of success. Determining whether such an alternating pattern is significant is a multiple-changepoint problem where the number of segments and their success probabilities are unknown, with the added constraint of segment alternation. A dynamic programming method for determining the optimal segmentation into a given number of segments is provided. Given this, a variation on the simulation method of Venter and Steel (1996, Computational Statistics and Data Analysis 22, 481-504) may be employed to test the null hypothesis of a homogeneous sequence as well as to estimate the number and location of changepoints. A sample application, the assessment of the possibility of genetic recombination in HIV sequences, is presented.

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Base SequenceGenes, envGenes, gagHIV-1HumansModels, GeneticModels, StatisticalMolecular Sequence DataRecombination, GeneticJournal ArticleResearch Support, Non-U.S. Gov'tResearch Support, U.S. Gov't, P.H.S.

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A L Halpern. 2000. Multiple-changepoint testing for an alternating segments model of a binary sequence.. https://doi.org/10.1111/j.0006-341x.2000.00903.x

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