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Markov chain Monte Carlo simulation using the DREAM software package: Theory, concepts, and MATLAB implementation

Environmental modelling & software : with environment data news, 2016-01, Vol.75, p.273-316

Vrugt, Jasper A.

2016

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High-dimensional posterior exploration of hydrologic models using multiple-try DREAM(ZS) and high-performance computing

Water resources research, 2012-01, Vol.48 (1), p.n/a

2012

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Toward diagnostic model calibration and evaluation: Approximate Bayesian computation

Water resources research, 2013-07, Vol.49 (7), p.4335-4345

2013

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Approximate Bayesian Computation using Markov Chain Monte Carlo simulation: DREAM(ABC)

Water resources research, 2014-08, Vol.50 (8), p.6767-6787

2014

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Towards a comprehensive assessment of model structural adequacy

Water resources research, 2012-08, Vol.48 (8), p.np-n/a

2012

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Improved evolutionary optimization from genetically adaptive multimethod search

Proceedings of the National Academy of Sciences - PNAS, 2007-01, Vol.104 (3), p.708-711

2007

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Present and future global distributions of the marine Cyanobacteria Prochlorococcus and Synechococcus

Proceedings of the National Academy of Sciences - PNAS, 2013-06, Vol.110 (24), p.9824-9829

2013

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Regional variation in the particulate organic carbon to nitrogen ratio in the surface ocean

Global biogeochemical cycles, 2013-09, Vol.27 (3), p.723-731

2013

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Hydrologic data assimilation using particle Markov chain Monte Carlo simulation: Theory, concepts and applications

Advances in water resources, 2013-01, Vol.51, p.457-478

2013

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Treatment of uncertainty using ensemble methods: Comparison of sequential data assimilation and Bayesian model averaging

Water resources research, 2007-01, Vol.43 (1), p.W01411-n/a

2007

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The Influence of Geostatistical Prior Modeling on the Solution of DCT-Based Bayesian Inversion: A Case Study from Chicken Creek Catchment

Remote sensing (Basel, Switzerland), 2019-07, Vol.11 (13), p.1549

2019

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Framework for Understanding Structural Errors (FUSE): A modular framework to diagnose differences between hydrological models

Water resources research, 2008-12, Vol.44 (12), p.W00B02-n/a

2008

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Concentrations and ratios of particulate organic carbon, nitrogen, and phosphorus in the global ocean

Scientific data, 2014-12, Vol.1 (1), p.140048-140048, Article 140048

2014

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Global-scale environmental control of plant photosynthetic capacity

Ecological applications, 2015-12, Vol.25 (8), p.2349-2365

2015

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Generalized likelihood uncertainty estimation (GLUE) using adaptive Markov Chain Monte Carlo sampling

Advances in water resources, 2008-04, Vol.31 (4), p.630-648

2008

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Distribution‐Based Model Evaluation and Diagnostics: Elicitability, Propriety, and Scoring Rules for Hydrograph Functionals

Water resources research, 2024-06, Vol.60 (6), p.n/a

Vrugt, Jasper A.

2024

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Improved treatment of uncertainty in hydrologic modeling: Combining the strengths of global optimization and data assimilation

Water resources research, 2005-01, Vol.41 (1), p.W01017-n/a

2005

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A formal likelihood function for parameter and predictive inference of hydrologic models with correlated, heteroscedastic, and non-Gaussian errors

Water resources research, 2010-10, Vol.46 (10), p.n/a

2010

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Significant uncertainty in global scale hydrological modeling from precipitation data errors

Journal of hydrology (Amsterdam), 2015-10, Vol.529, p.1095-1115

2015

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Soil hydraulic properties estimation from one‐dimensional infiltration experiments using characteristic time concept

Vadose zone journal, 2020, Vol.19 (1), p.n/a

2020

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Combining multiobjective optimization and Bayesian model averaging to calibrate forecast ensembles of soil hydraulic models

Water resources research, 2008-12, Vol.44 (12), p.W12432-n/a

2008

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Comparison of Three Multiobjective Optimization Algorithms for Inverse Modeling of Vadose Zone Hydraulic Properties

Soil Science Society of America journal, 2008-03, Vol.72 (2), p.305-319

2008

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A toolbox for the optimal design of run-of-river hydropower plants

Environmental modelling & software : with environment data news, 2019-01, Vol.111, p.134-152

2019

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Efficient posterior exploration of a high-dimensional groundwater model from two-stage Markov chain Monte Carlo simulation and polynomial chaos expansion

Water resources research, 2013-05, Vol.49 (5), p.2664-2682

2013

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Evaluation of subsurface drip irrigation design and management parameters for alfalfa

Agricultural water management, 2012-06, Vol.109, p.81-93

2012

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Markov chain Monte Carlo simulation using the DREAM software package: Theory, concepts, and MATLAB implementation

High-dimensional posterior exploration of hydrologic models using multiple-try DREAM(ZS) and high-performance computing

Toward diagnostic model calibration and evaluation: Approximate Bayesian computation

Approximate Bayesian Computation using Markov Chain Monte Carlo simulation: DREAM(ABC)

Towards a comprehensive assessment of model structural adequacy

Improved evolutionary optimization from genetically adaptive multimethod search

Present and future global distributions of the marine Cyanobacteria Prochlorococcus and Synechococcus

Regional variation in the particulate organic carbon to nitrogen ratio in the surface ocean

Hydrologic data assimilation using particle Markov chain Monte Carlo simulation: Theory, concepts and applications

Treatment of uncertainty using ensemble methods: Comparison of sequential data assimilation and Bayesian model averaging

The Influence of Geostatistical Prior Modeling on the Solution of DCT-Based Bayesian Inversion: A Case Study from Chicken Creek Catchment

Framework for Understanding Structural Errors (FUSE): A modular framework to diagnose differences between hydrological models

Concentrations and ratios of particulate organic carbon, nitrogen, and phosphorus in the global ocean

Global-scale environmental control of plant photosynthetic capacity

Generalized likelihood uncertainty estimation (GLUE) using adaptive Markov Chain Monte Carlo sampling

Distribution‐Based Model Evaluation and Diagnostics: Elicitability, Propriety, and Scoring Rules for Hydrograph Functionals

Improved treatment of uncertainty in hydrologic modeling: Combining the strengths of global optimization and data assimilation

A formal likelihood function for parameter and predictive inference of hydrologic models with correlated, heteroscedastic, and non-Gaussian errors

Significant uncertainty in global scale hydrological modeling from precipitation data errors

Soil hydraulic properties estimation from one‐dimensional infiltration experiments using characteristic time concept

Combining multiobjective optimization and Bayesian model averaging to calibrate forecast ensembles of soil hydraulic models

Comparison of Three Multiobjective Optimization Algorithms for Inverse Modeling of Vadose Zone Hydraulic Properties

A toolbox for the optimal design of run-of-river hydropower plants

Efficient posterior exploration of a high-dimensional groundwater model from two-stage Markov chain Monte Carlo simulation and polynomial chaos expansion

Evaluation of subsurface drip irrigation design and management parameters for alfalfa

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