Journal ArticleDOI
A comparison of sensitivity analysis and error analysis based on a stream ecosystem model
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In this article, it is suggested that the simple correlation coefficient derived from analysis of Monte Carlo simulations is a more reasonable way to rank model parameters according to their contribution to prediction uncertainty.About:
This article is published in Ecological Modelling.The article was published on 1981-04-01. It has received 164 citations till now. The article focuses on the topics: Variance-based sensitivity analysis & Sensitivity (control systems).read more
Citations
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A review of techniques for parameter sensitivity analysis of environmental models
TL;DR: Regression analysis provides the most comprehensive sensitivity measure and is commonly utilized to build response surfaces that approximate complex models.
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Water quality modeling: A review of the analysis of uncertainty
TL;DR: A review of the role of uncertainty in the identification of mathematical models of water quality and in the application of these models to problems of prediction can be found in this paper, where four problem areas are examined in detail: uncertainty about model structure, uncertainty in estimated model parameter values, the propagation of prediction errors, and the design of experiments in order to reduce the critical uncertainties associated with a model.
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Uncertainty and sensitivity analysis techniques for use in performance assessment for radioactive waste disposal
TL;DR: In this article, a review of uncertainty and sensitivity analysis techniques for use in performance assessments for radioactive waste disposal is presented. But, the most widely used technique for performance assessment is Monte Carlo analysis.
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An efficient method for parametric uncertainty analysis of numerical geophysical models
TL;DR: In this article, a new method for parametric uncertainty analysis of numerical geophysical models is presented, which approximates model response surfaces, which are functions of model input parameters, using orthogonal polynomials, whose weighting functions are the probabilistic density functions of the input uncertain parameters.
References
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Book
Applied Regression Analysis
Norman R. Draper,Harry Smith +1 more
TL;DR: In this article, the Straight Line Case is used to fit a straight line by least squares, and the Durbin-Watson Test is used for checking the straight line fit.
Book
A primer of multivariate statistics
TL;DR: A Primer of Multivariate Statistics as discussed by the authors provides a model of balance between how-to and why, with a focus on the importance of describing and testing one's interpretations of the emergent variables that are produced by multivariate analysis.
Journal ArticleDOI
Analysis of parameter error in a nonlinear model
TL;DR: In this paper, a two-variable nonlinear model was studied by randomly selecting parameters from independent triangular distributions, with maximum and minimum parameter values equal to 10% of the expected value.
Journal ArticleDOI
Application of error analysis to a Marsh Hydrology Model
TL;DR: In this article, the contribution of errors on individual parameters to uncertainties in model predictions is studied in a hydrologic model of a marsh, where daily values of water level and storage are calculated in the model as a function of precipitation, storm runoff from the urban watershed, physical properties of soil, groundwater movement, and daily value of evapotranspiration.