Search results for "State–space models"

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Information Transfer in Linear Multivariate Processes Assessed through Penalized Regression Techniques: Validation and Application to Physiological N…

2020

The framework of information dynamics allows the dissection of the information processed in a network of multiple interacting dynamical systems into meaningful elements of computation that quantify the information generated in a target system, stored in it, transferred to it from one or more source systems, and modified in a synergistic or redundant way. The concepts of information transfer and modification have been recently formulated in the context of linear parametric modeling of vector stochastic processes, linking them to the notion of Granger causality and providing efficient tools for their computation based on the state&ndash

conditional transfer entropyInformation transferlinear predictionDynamical systems theoryComputer scienceState–space modelsGeneral Physics and Astronomylcsh:AstrophysicsNetwork topologycomputer.software_genrenetwork physiology01 natural sciencesArticle03 medical and health sciences0302 clinical medicinepenalized regression techniquelcsh:QB460-4660103 physical sciencesEntropy (information theory)Statistics::Methodologylcsh:Science010306 general physicspartial information decompositionmultivariate time series analysisinformation dynamics; partial information decomposition; entropy; conditional transfer entropy; network physiology; multivariate time series analysis; State–space models; vector autoregressive model; penalized regression techniques; linear predictionState–space modellcsh:QC1-999multivariate time series analysiInformation dynamicData pointpenalized regression techniquesAutoregressive modelSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaParametric modelOrdinary least squaresvector autoregressive modellcsh:QData mininginformation dynamicsentropycomputerlcsh:Physics030217 neurology & neurosurgery
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