Premium
Multiple‐Changepoint Testing for an Alternating Segments Model of a Binary Sequence
Author(s) -
Halpern Aaron L.
Publication year - 2000
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/j.0006-341x.2000.00903.x
Subject(s) - sequence (biology) , binary number , constraint (computer aided design) , mathematics , alternation (linguistics) , segmentation , null hypothesis , sample (material) , statistical hypothesis testing , algorithm , homogeneous , computer science , statistics , combinatorics , artificial intelligence , arithmetic , biology , genetics , geometry , linguistics , philosophy , chemistry , chromatography
Summary. 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 t o 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.