Search results for "Nonlinear parametric model"

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Assessment of Granger causality by nonlinear model identification: application to short-term cardiovascular variability.

2007

A method for assessing Granger causal relationships in bivariate time series, based on nonlinear autoregressive (NAR) and nonlinear autoregressive exogenous (NARX) models is presented. The method evaluates bilateral interactions between two time series by quantifying the predictability improvement (PI) of the output time series when the dynamics associated with the input time series are included, i.e., moving from NAR to NARX prediction. The NARX model identification was performed by the optimal parameter search (OPS) algorithm, and its results were compared to the least-squares method to determine the most appropriate method to be used for experimental data. The statistical significance of…

Biomedical EngineeringBlood PressureBivariate analysisDirectionalitySensitivity and SpecificitySurrogate dataFeedbackNonlinear parametric modelGranger causalityControl theoryHeart RateOptimal parameter searchStatisticsAnimalsHumansComputer SimulationPredictabilityHeart rate variabilityMathematicsNonlinear autoregressive exogenous modelCardiovascular regulationSystem identificationModels CardiovascularNonlinear systemAutoregressive modelNonlinear DynamicsAutoregressive exogenous modelSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaRegression AnalysisSurrogate dataArterial pressure variabilityAlgorithmsAnnals of biomedical engineering
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