Please use this identifier to cite or link to this item: http://sutir.sut.ac.th:8080/jspui/handle/123456789/425
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dc.contributor.authorBoris I. Kvasov-
dc.date.accessioned2008-07-14T06:26:30Z-
dc.date.available2008-07-14T06:26:30Z-
dc.date.issued1995-
dc.identifier.citationRussian Journal of Numberical Analysis and Mathematical Modelling 10 (1995),No.1,pp 49-80,0en
dc.identifier.urihttp://sutir.sut.ac.th:8080/jspui/handle/123456789/425-
dc.descriptionผลงานวิชาการคณาจารย์มหาวิทยาลัยเทคโนโลยีสุรนารีen
dc.description.abstractPeriodic data are frequently collected in biomedical experiments. We consider the underlying periodic curves giving rise to these data, and account for the periodicity in their functional model to improve estimation and inference. We propose to incorporate the periodic constraint in the functional mixed-effects model setting. Both the fixed functional effects and random functional effects are modeled in the same periodic functional space, hence the population-average estimates and subject-specific predictions are all periodic. An efficient algorithm is given to estimate the proposed model by an O(N) modified Kalman filtering and smoothing algorithm. The proposed method is evaluated in different scenarios through simulations. Treatments to none-full period data and missing observations along the period are also given. Analysis of a cortisol data set obtained from a study on fibromyalgia is conducted as illustration.en
dc.format.extent332254 bytes-
dc.format.extent15570 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypeapplication/pdf-
dc.language.isoenen
dc.subjectgeneralizeden
dc.subjectcubic splineen
dc.titleLocal bass for generalized cubic splines.en
dc.typeArticleen
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