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Monte Carlo assessment of parameter uncertainty in conceptual catchment models: the Metropolis algorithm

Journal of Hydrology · 1998 · Vol. 211(1-4) · pp. 69–85

George Kuczera✉(University of Newcastle Australia)Éric Parent(Eau de Paris (France))

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Hydrology and Watershed Management Studies Groundwater flow and contamination studies Hydrology and Drought AnalysisMonte Carlo methodSampling (signal processing)Metropolis–Hastings algorithmComputer scienceGLUEProbability distributionSensitivity analysisUncertainty analysisImportance samplingStatistical inference

Funding

Australian Research Council

Citations

794

FWCI

18.82

field-weighted impact

References

33

Percentile

99%

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References

River flow forecasting through conceptual models part I — A discussion of principles

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Equation of State Calculations by Fast Computing Machines

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How much complexity is warranted in a rainfall‐runoff model?

Water Resources Research · 1993 · 1,193 citations

The future of distributed models: Model calibration and uncertainty prediction

Hydrological Processes · 1992 · 4,572 citations

Effective and efficient global optimization for conceptual rainfall‐runoff models

Water Resources Research · 1992 · 3,351 citations

Bayesian Inference in Statistical Analysis.

Journal of the American Statistical Association · 1975 · 3,873 citations

Time Series Analysis: Forecasting and Control

Journal of Marketing Research · 1977 · 19,299 citations

AN ESSAY TOWARDS SOLVING A PROBLEM IN THE DOCTRINE OF CHANCES

Biometrika · 1958 · 2,922 citations

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