Using time-delayed mutual information to discover and interpret temporal correlation structure in complex populations
| العنوان: | Using time-delayed mutual information to discover and interpret temporal correlation structure in complex populations |
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| المؤلفون: | David J. Albers, George Hripcsak |
| المصدر: | Chaos: An Interdisciplinary Journal of Nonlinear Science. 22:013111 |
| بيانات النشر: | AIP Publishing, 2012. |
| سنة النشر: | 2012 |
| مصطلحات موضوعية: | FOS: Computer and information sciences, Computer science, Computer Science - Information Theory, Population Dynamics, Population, Information Storage and Retrieval, FOS: Physical sciences, General Physics and Astronomy, Dynamical Systems (math.DS), computer.software_genre, Models, Biological, Methodology (stat.ME), FOS: Mathematics, Humans, Computer Simulation, Mathematics - Dynamical Systems, Time series, education, Statistics - Methodology, Mathematical Physics, Structure (mathematical logic), Sequence, education.field_of_study, Models, Statistical, Series (mathematics), Information Theory (cs.IT), Applied Mathematics, Aggregate (data warehouse), Statistical and Nonlinear Physics, Mutual information, Temporal correlation, Nonlinear Sciences - Chaotic Dynamics, Data mining, Chaotic Dynamics (nlin.CD), computer, Regular Articles |
| الوصف: | This paper addresses how to calculate and interpret the time-delayed mutual information (TDMI) for a complex, diversely and sparsely measured, possibly non-stationary population of time-series of unknown composition and origin. The primary vehicle used for this analysis is a comparison between the time-delayed mutual information averaged over the population and the time-delayed mutual information of an aggregated population (here, aggregation implies the population is conjoined before any statistical estimates are implemented). Through the use of information theoretic tools, a sequence of practically implementable calculations are detailed that allow for the average and aggregate time-delayed mutual information to be interpreted. Moreover, these calculations can also be used to understand the degree of homo or heterogeneity present in the population. To demonstrate that the proposed methods can be used in nearly any situation, the methods are applied and demonstrated on the time series of glucose measurements from two different subpopulations of individuals from the Columbia University Medical Center electronic health record repository, revealing a picture of the composition of the population as well as physiological features. |
| تدمد: | 1089-7682 1054-1500 |
| الوصول الحر: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b07784dcad8eb884192694eaead26b92Test https://doi.org/10.1063/1.3675621Test |
| حقوق: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....b07784dcad8eb884192694eaead26b92 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 10897682 10541500 |
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