The sensitivity analysis over the page illustrates the potential impact on the income statement and equity for reasonably possible. However their estimation requires a large number of model evaluations, especially when interaction effects are of interest. Sensitivity analysis sobol indices morris method model derivatives dgsm poincare inequality. Salib sensitivity analysis library in python salib 1. For the purpose of identifying the influential distribution parameters, the parametric sensitivity of im on the failure probability based on local and global sensitivity analysis technology is proposed. In addition, the board may choose to establish limits relative to earnings, total assets, total investment securities, or. Derivativebased global sensitivity measures dgsm have recently shown their efficiency for the identification of. For the development and the analyses of such computer models, the global sensitivity. Sixth international conference on sensitivity analysis of model output. Derivativebased global sensitivity measures springerlink.
Sobol indices are now classical sensitivity measures. Derivative based global sensitivity measures arxiv. Partial derivativebased sensitivity analysis of models. Sensitivity analysis is an analysis method that is used to identify how much variations in the input values for a given variable will impact the results for a mathematical model. Derivative based sensitivity analysis of gamma index. Derivative based sensitivity analysis of gamma index core. Estimation of the derivativebased global sensitivity. Derivativebased global sensitivity measures archive ouverte hal. The socalled derivativebased global sensitivity measures dgsm 2 consist, for. For this comparison, 4 biotechnological models with varying model complexity were used.
The momentindependent importance measure im on the failure probability is important in system reliability engineering, and it is always influenced by the distribution parameters of inputs. In this paper we consider partial derivative based global sensitivity measures and. This technique is compared to the finite difference approximation, probably the most used local sensitivity analysis technique. Sensitivity analysis, estimating derivatives and the greeks. Scenario analysis project analysis given a particular combination of assumptions. Stability and resolution analysis of topological derivative based localization of. One use for the approach is the optimization of an experimental design enabling estimation of model parameters with improved.
Sensitivity analysis can also indicate which parameter values are. The proposed technique employs a biophysically derived model for parameter fluctuations and, by using a recently suggested variancebased approach to sensitivity analysis saltelli et al. In this paper we propose an extension of the classical sobol estimator for the estimation of variance based sensitivity indices. Useful in systems modeling to calculate the effects of model inputs or exogenous factors on outputs of interest. Sensitivity analysis, estimating derivatives and the greeks estimating the sensitivity of a simulation with respect to changes in the parameter values is an important part of establishing the validity of the conclusions.
We present a framework for derivativebased global sensitivity analysis gsa for models with highdimensional input parameters and functional outputs. Gamma analysis does not account for the gradient of the evaluated curve it looks at only the minimum gamma value, and if it is. For the traditional variancebased global sensitivity analysis, the total effect of individual variable commonly involves the interactions with other variables. Often the parameter space to be investigated is enormous. This method provides sampling matrices following the original joint probability. If the tests reveal that the model is insensitive, then it may be possible to use an estimate rather than a value with greater precision. It can be seen as the generalization of the morris method. Derivative based global sensitivity measures and their link with global sensitivity indices. Global sensitivity analysis gsa methods sobol 20, saltelli et al. Derivativebased global sensitivity analysis for models with.
Pdf we introduce new global sensitivity measures called derivative based global. Derivative based global sensitivity measures abstract the method of derivative based global sensitivity measures dgsm has recently become popular among practitioners. The proposed derivativebased method can identify a noisy curve and can prove to be a useful tool for improving the sensitivity of the gamma index. Tanaka surveyed the sensitivity analysis in the scope of multivariate data analysis 30. Sensitivity analysis analysis of the effects of changes in sales, costs, etc. Most commercial lp solvers provide such information. Partial derivativebased sensitivity analysis of models describing targetmediated drug disposition. This simplifying assumption is made to facilitate the subsequent variancebased sensitivity analysis even though the geometrical properties characterizing a pore. Sensitivity analysis allows him to determine what level of accuracy is necessary for a parameter to make the model sufficiently useful and valid. This is simple information about how much certain coefficients can change before the current optimum solution is fundamentally changed. Parametric sensitivity analysis for importance measure on.
Capitalbased risk limits clearly illustrate the potential threat to the banks viability, while earningsbased limits reflect potential profitability effects. Topological sensitivity analysis for the modified helmholtz equation under an impedance condition on the boundary of a hole. Break even analysis analysis of the level of sales or other variable at which the. What remains, as in the rst derivation, is d pf tg p. In this introductory book, we will concentrate on this form of sensitivity analysis. Since the distribution parameters of variables are difficult to be given precisely, this work defines the derivativebased sensitivity of variance contribution with respect to the. Pdf derivative based sensitivity analysis of gamma index.
In this paper, the complexstep derivative approximation technique will be used for calculating local sensitivity functions. If a simulation estimates an expected value at certain value of the parameters. Market risk market risk refers to the sensitivity of an asset or portfolio to overall market price movements such as interest rates. Derivative based global sensitivity measures and their link. The primary objective of this study is to conduct a sensitivity analysis of selected targetmediated pharmacokinetic models, ascertain the effect of. Sensitivity analysis, sobol indices, morris method, model deriva. The method of derivative based global sensitivity measures dgsm has recently. A new global sensitivity measure based on derivative. Simulation analysis estimation of the distribution of different possible outcomes. Variancebased global sensitivity analysis sa methods require a large number of function evaluations to achieve acceptable convergence and can become. Trajectory modulated arc therapy using quasicontinuous couch motion layered on. Although there are various uses for sensitivity information, our main motivation is the use of this information in gradientbased optimization. Derivativebased global sensitivity measure dgsm sobol and kucherenko 2009 fractional factorial sensitivity analysis saltelli et al.
To further decompose the interactive effects, this paper proposes a new global sensitivity measure based on derivativeintegral and variance decomposition. Variancebased global sensitivity analysis sa methods require a large. For many years now, other tools have been studied, closer to physical practices such as the derivativebased global sensitivity measures dgsm. Pdf derivative based global sensitivity measures researchgate. Sensitivity analysis is commonly used to characterize the effects of parameter perturbations on model output. Variancebased sensitivity analysis in the presence of. Variancebased sensitivity analysis with dependent variables represents how the uncertainties and dependence of variables influence the output uncertainty.
Global sensitivity analysis of multiscale properties of. The approach assumes a linear correlation model between the input variables which is used to decompose the contribution of an input variable into a correlated and an uncorrelated part. Pdf avoiding the finite difference sensitivity analysis. Firstly, the firstorder sensitivity index only relating to individual variable. We introduce new global sensitivity measures called derivative based global sensitivity measures dgsm. Monte carlo based sensitivity analysis and derivativefree. One use for the approach is the optimization of an experimental design enabling estimation of model parameters with improved accuracy. Methods such as linear sensitivity analysis or the global morris method can be used for screening out unimportant parameters before more complex global sensitivity methods are used. Between these two extremes is computerbased ranging. Derivative, dose distribution comparison, gamma index, radiotherapy, sensitivity, sensitivity analysis. Sobol indices, based on output variance decomposition, are commonly used to perform quantitative gsa.
Derivative based global sensitivity measures sciencedirect. As derivative strategies have become more commonplace, risk regulation has tightened. It has a strong link with the morris screening method and sobol sensitivity indices and has several advantages over them. We also show that there is a link between dgsm and sobol total sensitivity indices which makes this approach theoretically sound and general. Global sensitivity indices for nonlinear mathematical models and their monte carlo estimates. Since the distribution parameters of variables are difficult to be given precisely, this work defines the derivativebased sensitivity of variance contribution with respect to the distribution parameters. Design sensitivity analysis for shape optimization based.
905 1004 839 1337 1643 651 1558 29 1427 1014 13 86 356 319 347 797 795 1293 278 1502 1325 309 49 1392 1201 1425 240 1609 966 1141 900 974 1189 242 145 842 516 1502 650 1134 425 1033 850 1154 1025 783 1049 632 1481 892