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Framework for Adaptive Multiscale Analysis of Nonhomogeneous Point Processes
KTH, School of Electrical Engineering (EES), Sound and Image Processing.
2011 (English)In: 2011 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), New York: IEEE , 2011, 7727-7730 p.Conference paper, Published paper (Refereed)
Abstract [en]

We develop the methodology for hypothesis testing and model selection in nonhomogeneous Poisson processes, with an eye toward the application of modeling and variability detection in heart beat data. Modeling the process' non-constant rate function using templates of simple basis functions, we develop the generalized likelihood ratio statistic for a given template and a multiple testing scheme to model-select from a family of templates. A dynamic programming algorithm inspired by network flows is used to compute the maximum likelihood template in a multiscale manner. In a numerical example, the proposed procedure is nearly as powerful as the super-optimal procedures that know the true template size and true partition, respectively. Extensions to general history-dependent point processes is discussed.

Place, publisher, year, edition, pages
New York: IEEE , 2011. 7727-7730 p.
Keyword [en]
point processes, nonhomogeneous Poisson processes, nonparametric detection, dynamic programming, multiple comparisons, heart rate analysis
National Category
Medical and Health Sciences
Identifiers
URN: urn:nbn:se:kth:diva-92080ISI: 000298810005308Scopus ID: 2-s2.0-84055223487ISBN: 978-1-4244-4122-8 (print)OAI: oai:DiVA.org:kth-92080DiVA: diva2:512001
Conference
33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011;Boston, MA; 30 August 2011 through 3 September 2011
Note
QC 20120326Available from: 2012-03-26 Created: 2012-03-26 Last updated: 2012-03-26Bibliographically approved

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