| Estimation of time-delayed mutual information and bias for irregularly and sparsely sampled time-series. | |
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MedLine Citation:
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PMID: 22536009 Owner: NLM Status: Publisher |
Abstract/OtherAbstract:
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A method to estimate the time-dependent correlation via an empirical bias estimate of the time-delayed mutual information for a time-series is proposed. In particular, the bias of the time-delayed mutual information is shown to often be equivalent to the mutual information between two distributions of points from the same system separated by infinite time. Thus intuitively, estimation of the bias is reduced to estimation of the mutual information between distributions of data points separated by large time intervals. The proposed bias estimation techniques are shown to work for Lorenz equations data and glucose time series data of three patients from the Columbia University Medical Center database. |
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Authors:
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D J Albers; George Hripcsak |
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Publication Detail:
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Type: JOURNAL ARTICLE |
Journal Detail:
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Title: Chaos, solitons, and fractals Volume: 45 ISSN: 0960-0779 ISO Abbreviation: - Publication Date: 2012 Jun |
Date Detail:
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Created Date: 2012-4-26 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 100971564 Medline TA: Chaos Solitons Fractals Country: - |
Other Details:
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Languages: ENG Pagination: 853-860 Citation Subset: - |
Affiliation:
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Department of Biomedical Informatics, Columbia University, 622 W 168 St. VC-5, New York, NY 10032. |
Export Citation:
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Descriptor/Qualifier:
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| Grant Support | |
ID/Acronym/Agency:
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R01 LM006910-11/LM/NLM NIH HHS |
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