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This article presents applications of multivariate autoregression (MVAR) modeling for analyzing the interaction between EEG and EMG, which is challenging because of their different modalities.
The purpose of this paper is to describe ongoing research work into the development of a simulation system that integrates statistical analysis, simulation and visualization with computer modeling for analyzing the complex human environment interactions in dynamic settings.
Nagin [ 6, 7] described a semiparametric, group-based approach based on finite mixture modeling for analyzing behavioral development trajectories.
The reconstruction of the geographic range history was performed in Lagrange [ 26], which uses a dispersal-extinction-cladogenesis (DEC) modeling for analyzing ML probabilities of rate transitions as a function of time.
This work is based on an earlier work: "Rule-based whole body modeling for analyzing multi-compound effects", in Proceedings of the ACM Sixth International Workshop on Data and Text Mining in Biomedical Informatics, 2012 © ACM, 2012.
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