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标题：Statistical Shape Methodology for the Analysis of Helices
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作者：Mai F. Alfahad ; John T. Kent ; Kanti V. Mardia 等
期刊名称：Sankhya. Series A, mathematical statistics and probability
印刷版ISSN：0976-836X
电子版ISSN：0976-8378
出版年度：2018
页码：1-25
DOI：10.1007/s13171-018-0144-8
语种：English
出版社：Indian Statistical Institute
摘要：Consider a helix in three-dimensional space along which a sequence of equally spaced points is observed, subject to statistical noise. For data coming from a single helix, a two-stage algorithm based on a profile likelihood is developed to compute the maximum likelihood estimate of the helix parameters. Statistical properties of the estimator are studied and comparisons are made to other estimators found in the literature. Next a likelihood ratio test is developed to test if there is a change point in the helix, splitting the data into two sub-helices. The shapes of protein α -helices are used to illustrate the methodology.
关键词：Change point ; Helix axis ; Kinked helix ; Principal component analysis ; Procrustes analysis ; Shape analysis