Data-driven simulation of complex multidimensional time series
Schruben, Lee W.
Singham, Dashi I.
MetadataShow full item record
This article introduces a new framework for resampling general time series data. The approach, inspired by computer agent flocking algorithms, can be used to generate inputs to complex simulation models or for generating pseudo-replications of expensive simulation outputs. The method has the flexibility to enable replicated sensitivity analysis for trace-driven simulation, which is critical for risk assessment. The article includes two simple implementations to illustrate the approach. These implementations are applied to nonstationary and state-dependent multivariate time series. Examples using emergency department data are presented.
The article of record as published may be found at: http//:dx.doi.org/10.1145.2553082
RightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
Showing items related by title, author, creator and subject.
Countering Disinformation Propaganda: Reverse Engineering the Experimental Implicit Learning Paradigm Canan, Mustafa; Canan, Daphne (Academic Conferences International Limited, 2020);A conflict may develop when people ascribe different meanings to shared phenomena that entail action. In simple situations, resolution can be by persuading the other actors so that actions converge. In complex situations, ...
Russell, Lynn M.; Sorooshian, Armin; Seinfeld, John H.; Albrecht, Bruce A.; Nenes, Athanasios; Ahlm, Lars; Chen, Yi-Chun; Coggon, Matthew; Craven, Jill S.; Flagan, Richard C.; Frossard, Amanda A.; Jonsson, Haflidi; Jung, Eunsil; Lin, Jack J.; Metcalf, Andrew R.; Modini, Robin; Mülmlmenstädt, Johannes; Roberts, Greg C.; Shingler, Taylor; Song, Siwon; Wang, Zhen; Wonaschütz, Anna (2013-05);E-PEACE analyzed aircraft and satellite measurements to separate the aerosol cloud effects of three synthetic particle sources from dynamical variability.