J
Jasper A. Vrugt
Researcher at University of California, Irvine
Publications - 171
Citations - 20224
Jasper A. Vrugt is an academic researcher from University of California, Irvine. The author has contributed to research in topics: Markov chain Monte Carlo & Hydrological modelling. The author has an hindex of 60, co-authored 159 publications receiving 17719 citations. Previous affiliations of Jasper A. Vrugt include Los Alamos National Laboratory & Forschungszentrum Jülich.
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Journal ArticleDOI
A Shuffled Complex Evolution Metropolis algorithm for optimization and uncertainty assessment of hydrologic model parameters
TL;DR: Three case studies demonstrate that the adaptive capability of the SCEM‐UA algorithm significantly reduces the number of model simulations needed to infer the posterior distribution of the parameters when compared with the traditional Metropolis‐Hastings samplers.
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Accelerating Markov chain Monte Carlo simulation by differential evolution with self-adaptive randomized subspace sampling
TL;DR: The DREAM scheme significantly enhances the applicability of MCMC simulation to complex, multi-modal search problems andErgodicity of the algorithm is proved, and various examples involving nonlinearity, high-dimensionality, and multimodality show that DREAM is generally superior to other adaptive MCMC sampling approaches.
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Present and future global distributions of the marine Cyanobacteria Prochlorococcus and Synechococcus
Pedro Flombaum,José L. Gallegos,Rodolfo A. Gordillo,José Rincon,Lina L. Zabala,Nianzhi Jiao,David M. Karl,William K. W. Li,Michael W. Lomas,Daniele Veneziano,Carolina Vera,Jasper A. Vrugt,Adam C. Martiny +12 more
TL;DR: The global niche models suggest that oceanic microbial communities will experience complex changes as a result of projected future climate conditions, and these changes may have large impacts on ocean ecosystems and biogeochemical cycles.
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Treatment of input uncertainty in hydrologic modeling: doing hydrology backward with Markov chain Monte Carlo simulation.
Jasper A. Vrugt,Jasper A. Vrugt,Cajo J. F. ter Braak,Martyn P. Clark,James M. Hyman,Bruce A. Robinson +5 more
TL;DR: A novel Markov chain Monte Carlo (MCMC) sampler, entitled differential evolution adaptive Metropolis (DREAM), that is especially designed to efficiently estimate the posterior probability density function of hydrologic model parameters in complex, high-dimensional sampling problems.