Variance Based Sensitivity Analysis
Using a variance-based sensitivity analysis for analyzing the relation between measurements and unknown parameters of a physical model
... the sensitivity concern- ing the mass and the energy for the objective function con- cerning the gravity changes are quite different compared to the other objective ...concrete analysis of mass and energy ...
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Variance-based sensitivity analysis in vehicle dynamics simulation: development and application of a polynomial chaos expansion method
... system based on components, containing dif- ferent multi-body axle models including axle geometry via hardpoint definition or tabled axle kinematics, various steering and drivetrain configurations and the TM-Easy ...
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Variance Based Sensitivity Analysis of IKrIKr in a Model of the Human Atrial Action Potential Using Gaussian Process Emulators
... Abstract. Cardiac cell models have become valuable research tools, but biophysically detailed models embed large numbers of parameters, which must be fitted from experimental data. The provenance of these param- eters ...
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Temporal Variance-Based Sensitivity Analysis of the River-Routing Component of the Large-Scale Hydrological Model ISBA–TRIP: Application on the Amazon Basin
... a sensitivity analysis based on the decomposition of model output variance (using a method called ANOVA) is utilized and applied over the Amazon ...height variance with purely additive ...
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Sensitivity Analysis Using Sobol' Variance-Based Method on the Haverkamp Constitutive Functions Implemented in Richards' Water Flow Equation
... established based on significant digits approximation. The variance-based sensitivity analysis was carried out on Haverkamp constitutive functions to determine the first order ...
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Toward a more robust variance-based global sensitivity analysis of model outputs
... output variance is possible (for independent input factors). These variance components are called Sobol’ indices, and can be used for any complex model ...“total sensitivity indices” which can be ...
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Comparison of variance-based and moment-independent global sensitivity analysis approaches by application to the SWAT model
... 12 that for the model parameters, the value of the considered parameter remains unchanged for the conditional distribution. Therefore, for the dummy parameter, the unconditional and conditional random samples are from ...
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Asset allocation in the Athens Stock Exchange: A variance sensitivity analysis
... an analysis of asset allocation using univariate portfolio GARCH models from the Athens Stock ...Our analysis adopts the methodology due to Manganelli (2004) and we are able to recover from the univariate ...
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Incorporating output variance in local sensitivity analysis for stochastic models
... Local sensitivity analyses of such models typically ignore the higher moments of the output distribution and instead use the distribution mean to rep- resent model ...simple sensitivity index that captures ...
Variance-based sensitivity indices of computer models with dependent inputs: The Fourier Amplitude Sensitivity Test
... global sensitivity analysis of computer models with independent ...compute variance-based sensitivity indices with the Fourier amplitude sensitivity ...Carlo based ...
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FLIP-MHD-based model sensitivity analysis
... the variance remains very low, it can be noted here that the en- semble variance evolution is quite similar for the six loca- tions: the variance of the ensemble is extremely low at the beginning of ...
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Reference Based Sensitivity Analysis for Time-to-Event Data
... the sensitivity analysis relative to the primary ...all sensitivity analysis methods, the aim is to assess the behaviour of the treatment estimate under alternative, clinically plausible, ...
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A GIS-Based Sensitivity Analysis of Multi-Criteria Weights
... Carlo analysis, from measures of importance to sensitivity indices, from regression or correlation methods to variance-based techniques (Archer et ...
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Sensitivity Analysis of Minimum Variance Portfolios
... The optimal portfolio is chosen by the investor with the best market information he or his agent could obtain. There are several reasons why we need to consider the sensitivities of the portfolio to its parameters. First ...
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AN APPROXIMATION OF THE MINIMUM-VARIANCE ESTIMATOR OF HERITABILITY BASED ON VARIANCE COMPONENT ANALYSIS
... was the estimate of heritability significantly different from expectation for the parameter set with lowest heritability and population size. Constraining the estimates [r] ...
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Chapter 5 Analysis of variance SPSS Analysis of variance
... Your goal is to determine whether the interaction observed in the sample is large enough to believe that it also exists in the population. The table ‘Between-Subjects Factors’ speaks for itself. The table ‘Tests of ...
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Analysis of Variance
... effective. Analysis of Variance of 2-way Classification Model: When 2 independent factors might affect the variable of interest it is possible to design a test so that an analysis of variance ...
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Variance Analysis
... Globusz ® Publishing Chapter 5 Variance Analysis A variance is the difference between an actual result and an expected result. The process by which the total difference between standard and actual ...
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Analysis of variance
... of variance explained by a batch of predictors in a regression depends on which other variables have already been included in the ...the variance decomposition does not depend on the order in which the ...
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Theoretical and empirical estimates of mean-variance portfolio sensitivity
... investor maximizes the objective function (utility) B(w) = µ T w − γ 2 w T Σw, (1) where w denotes portfolio holdings specified in terms of fractions of the wealth, and the constant γ > 0 is the investor’s risk aversion ...
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