Academic literature on the topic 'Sensitivity indices'
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Journal articles on the topic "Sensitivity indices"
Lamboni, Matieyendou. "Derivative-based generalized sensitivity indices and Sobol’ indices." Mathematics and Computers in Simulation 170 (April 2020): 236–56. http://dx.doi.org/10.1016/j.matcom.2019.10.017.
Full textXu, Chonggang, and George Zdzislaw Gertner. "Reliability of global sensitivity indices." Journal of Statistical Computation and Simulation 81, no. 12 (December 2011): 1939–69. http://dx.doi.org/10.1080/00949655.2010.509317.
Full textDa Veiga, Sébastien, and Fabrice Gamboa. "Efficient estimation of sensitivity indices." Journal of Nonparametric Statistics 25, no. 3 (September 2013): 573–95. http://dx.doi.org/10.1080/10485252.2013.784762.
Full textGamboa, Fabrice, Alexandre Janon, Thierry Klein, and Agnès Lagnoux. "Sensitivity indices for multivariate outputs." Comptes Rendus Mathematique 351, no. 7-8 (April 2013): 307–10. http://dx.doi.org/10.1016/j.crma.2013.04.016.
Full textIzsák, János. "Sensitivity Profiles of Diversity Indices." Biometrical Journal 38, no. 8 (1996): 921–30. http://dx.doi.org/10.1002/bimj.4710380804.
Full textMacArthur, Lauren A. "Dust Sensitivity of Absorption‐Line Indices." Astrophysical Journal 623, no. 2 (April 20, 2005): 795–814. http://dx.doi.org/10.1086/428827.
Full textJanon, Alexandre, Maëlle Nodet, and Clémentine Prieur. "Certified metamodels for sensitivity indices estimation." ESAIM: Proceedings 35 (March 2012): 234–38. http://dx.doi.org/10.1051/proc/201235020.
Full textSalome, C. M., N. J. Brown, H. K. Reddel, W. Xuan, and G. B. Marks. "Indices of bronchial reactivity and sensitivity." Thorax 66, no. 3 (October 27, 2010): 265–66. http://dx.doi.org/10.1136/thx.2010.151639.
Full textChung, C. Y., C. T. Tse, R. Niu, and K. W. Wang. "PSS Design by Probabilistic Sensitivity Indices." IEEE Power Engineering Review 22, no. 7 (July 2002): 56. http://dx.doi.org/10.1109/mper.2002.4312394.
Full textLasersohn, Peter. "Non-World Indices and Assessment-Sensitivity." Inquiry 56, no. 2-3 (April 2013): 122–48. http://dx.doi.org/10.1080/0020174x.2013.784463.
Full textDissertations / Theses on the topic "Sensitivity indices"
GIOIA, PAOLA. "Towards more accurate measures of global sensitivity analysis. Investigation of first and total order indices." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2013. http://hdl.handle.net/10281/45695.
Full textFernandez, Chas Margarita. "Insulin sensitivity estimates from a linear model of glucose disappearance." Thesis, University of Sussex, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.341544.
Full textMoore, Alan D. "Reproducibility and sensitivity of Doppler echocardiographic indices of left ventricular function during exercise." Diss., Virginia Polytechnic Institute and State University, 1987. http://hdl.handle.net/10919/53648.
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Wajahat, Qazi Hassan. "Development of Sensitivity Based Indices for Optimal Placement of UPFC to Minimize Load Curtailment Requirements." Thesis, KTH, Elektriska energisystem, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-119252.
Full textChastaing, Gaëlle. "Indices de Sobol généralisés par variables dépendantes." Thesis, Grenoble, 2013. http://www.theses.fr/2013GRENM046.
Full textA mathematical model aims at characterizing a complex system or process that is too expensive to experiment. However, in this model, often strongly non linear, input parameters can be affected by a large uncertainty including errors of measurement of lack of information. Global sensitivity analysis is a stochastic approach whose objective is to identify and to rank the input variables that drive the uncertainty of the model output. Through this analysis, it is then possible to reduce the model dimension and the variation in the output of the model. To reach this objective, the Sobol indices are commonly used. Based on the functional ANOVA decomposition of the output, also called Hoeffding decomposition, they stand on the assumption that the incomes are independent. Our contribution is on the extension of Sobol indices for models with non independent inputs. In one hand, we propose a generalized functional decomposition, where its components is subject to specific orthogonal constraints. This decomposition leads to the definition of generalized sensitivity indices able to quantify the dependent inputs' contribution to the model variability. On the other hand, we propose two numerical methods to estimate these constructed indices. The first one is well-fitted to models with independent pairs of dependent input variables. The method is performed by solving linear system involving suitable projection operators. The second method can be applied to more general models. It relies on the recursive construction of functional systems satisfying the orthogonality properties of summands of the generalized decomposition. In parallel, we illustrate the two methods on numerical examples to test the efficiency of the techniques
Horiguchi, Akira. "Bayesian Additive Regression Trees: Sensitivity Analysis and Multiobjective Optimization." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1606841319315633.
Full textMasinde, Brian. "Birds' Flight Range. : Sensitivity Analysis." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-166248.
Full textSeol, Huynsoo. "Sensitivity of five Rasch-model-based fit indices to selected person and item aberrances : a simulation study /." The Ohio State University, 1998. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487949508369046.
Full textHeredia, Guzman Maria Belen. "Contributions to the calibration and global sensitivity analysis of snow avalanche numerical models." Thesis, Université Grenoble Alpes, 2020. http://www.theses.fr/2020GRALU028.
Full textSnow avalanche is a natural hazard defined as a snow mass in fast motion. Since the thirties, scientists have been designing snow avalanche models to describe snow avalanches. However, these models depend on some poorly known input parameters that cannot be measured. To understand better model input parameters and model outputs, the aims of this thesis are (i) to propose a framework to calibrate input parameters and (ii) to develop methods to rank input parameters according to their importance in the model taking into account the functional nature of outputs. Within these two purposes, we develop statistical methods based on Bayesian inference and global sensitivity analyses. All the developments are illustrated on test cases and real snow avalanche data.First, we propose a Bayesian inference method to retrieve input parameter distribution from avalanche velocity time series having been collected on experimental test sites. Our results show that it is important to include the error structure (in our case the autocorrelation) in the statistical modeling in order to avoid bias for the estimation of friction parameters.Second, to identify important input parameters, we develop two methods based on variance based measures. For the first method, we suppose that we have a given data sample and we want to estimate sensitivity measures with this sample. Within this purpose, we develop a nonparametric estimation procedure based on the Nadaraya-Watson kernel smoother to estimate aggregated Sobol' indices. For the second method, we consider the setting where the sample is obtained from acceptance/rejection rules corresponding to physical constraints. The set of input parameters become dependent due to the acceptance-rejection sampling, thus we propose to estimate aggregated Shapley effects (extension of Shapley effects to multivariate or functional outputs). We also propose an algorithm to construct bootstrap confidence intervals. For the snow avalanche model application, we consider different uncertainty scenarios to model the input parameters. Under our scenarios, the release avalanche position and volume are the most crucial inputs.Our contributions should help avalanche scientists to (i) account for the error structure in model calibration and (ii) rankinput parameters according to their importance in the models using statistical methods
Tissot, Jean-yves. "Sur la décomposition ANOVA et l'estimation des indices de Sobol'. Application à un modèle d'écosystème marin." Thesis, Grenoble, 2012. http://www.theses.fr/2012GRENM064/document.
Full textIn the fields of modelization and numerical simulation, simulators generally depend on several input parameters whose impact on the model outputs are not always well known. The main goal of sensitivity analysis is to better understand how the model outputs are sensisitive to the parameters variations. One of the most competitive method to handle this problem when complex and potentially highly non linear models are considered is based on the ANOVA decomposition and the Sobol' indices. More specifically the latter allow to quantify the impact of each parameters on the model response. In this thesis, we are interested in the issue of the estimation of the Sobol' indices. In the first part, we revisit in a rigorous way existing methods in light of discrete harmonic analysis on cyclic groups and randomized orthogonal arrays. It allows to study theoretical properties of this method and to intriduce generalizations. In a second part, we study the Monte Carlo method for the Sobol' indices and we introduce a new approach to reduce the number of simulations of this method. In parallel with this theoretical work, we apply these methods on a marine ecosystem model
Books on the topic "Sensitivity indices"
B, Baldwin David J., and Ontario Forest Research Institute, eds. Sensitivity of landscape pattern indices to spatial extent, data resolution, and classification detail in the managed forest of Ontario. Sault Ste. Marie, Ont: Ontario Forest Research Institute, 2001.
Find full textMalik, Waleed Haider. Cultural sensitivity: Judges in indigenous areas. Washington, D.C: World Bank, 2003.
Find full textKumar, C. Nalin. Sensitivity of India's agri-food exports to the European Union: An institutional perspective. Bangalore: Institute for Social and Economic Change, 2016.
Find full textMona, Charles, Fort Lewis College. Dept. of Anthropology., Midwest Archeological Center (U.S.), and Fort Carson (Colo.). Directorate of Environmental Compliance and Management., eds. A cultural resource inventory of high- and medium- site sensitivity areas, Fort Carson Military Reservation: El Paso, Fremont, and Pueblo Counties, Colorado, 1998. [Lincoln, Neb: Midwest Archeological Center, 2000.
Find full textDuclos, Jean-Yves, and Luca Tiberti. Multidimensional Poverty Indices. Edited by Matthew D. Adler and Marc Fleurbaey. Oxford University Press, 2016. http://dx.doi.org/10.1093/oxfordhb/9780199325818.013.19.
Full textFacemire, Charles F. Comparison of the sensitivity of electrophoresis and ecological indices for the detection of environmental stress in aquatic ecosystems. 1989.
Find full textRosik, Piotr. Świat dostępności - metody i komponenty : przykłady analiz empirycznych przestrzeni Polski = The world of accessibility : methods and components : cases of emprical analyses in Poland's space. Instytut Geografii i Przestrzennego Zagospodarowania im. Stanisława Leszczyckiego, Polska Akademia Nauk, 2021. http://dx.doi.org/10.7163/9788361590767.
Full textPelto, Joan McAlmond. Field sensitivity of Native American students at Oregon State University, as determined by the group embedded figures test. 1991.
Find full textWeinberg, Jonathan M. Knowledge, Noise, and Curve-Fitting. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198724551.003.0016.
Full textKing, Anna S., ed. Indian Religions: Renaissance and Renewal. Equinox Publishing, 2007. http://dx.doi.org/10.1558/isbn.9781845531690.
Full textBook chapters on the topic "Sensitivity indices"
Mandel, David, and Giray Ökten. "Randomized Sobol’ Sensitivity Indices." In Springer Proceedings in Mathematics & Statistics, 395–408. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91436-7_22.
Full textTurnovec, František, and Jacek Mercik. "Sensitivity Analysis of a Priori Power Indices." In Intelligent Information and Database Systems, 464–73. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-05476-6_47.
Full textKucherenko, Sergei, and Shugfang Song. "Derivative-Based Global Sensitivity Measures and Their Link with Sobol’ Sensitivity Indices." In Springer Proceedings in Mathematics & Statistics, 455–69. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-33507-0_23.
Full textGottschalk, Alexander, Eugene Cornelius, and Paul B. Hoffer. "Sensitivity and Efficacy Indices for Oncologic Data Reporting." In Radiolabeled Monoclonal Antibodies for Imaging and Therapy, 139–45. Boston, MA: Springer US, 1988. http://dx.doi.org/10.1007/978-1-4684-5538-0_11.
Full textFedotov, A. A., and A. S. Akulova. "Sensitivity of heart rate variability indices for artificially simulated data." In IFMBE Proceedings, 945–49. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-19387-8_230.
Full textSpiring, Fred. "The Sensitivity of Common Capability Indices to Departures from Normality." In Frontiers in Statistical Quality Control 9, 277–93. Heidelberg: Physica-Verlag HD, 2010. http://dx.doi.org/10.1007/978-3-7908-2380-6_18.
Full textObrist, W. D., and W. E. Wilkinson. "Stability and Sensitivity of CBF Indices in the Noninvasive 133Xe Method." In Cerebral Blood Flow and Metabolism Measurement, 30–36. Berlin, Heidelberg: Springer Berlin Heidelberg, 1985. http://dx.doi.org/10.1007/978-3-642-70054-5_4.
Full textChervenkov, Hristo, and Valery Spiridonov. "Sensitivity of Selected ETCCDI Climate Indices from the Calculation Method for Projected Future Climate." In Advances in High Performance Computing, 413–27. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-55347-0_35.
Full textJain, Rinkesh A., and Darshan B. Rathod. "Line Stability Indices and Contingency Screening by Sensitivity Factors Based Static Voltage Stability Study." In Advances in Intelligent Systems and Computing, 129–38. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1966-2_11.
Full textPerkins, Kyle, and Worthen N. Hunsaker. "A Comparison of Bayesian and Traditional Indices for Measuring Information Gain Sensitivity in a Cloze Test." In Language Proficiency, 163–71. Boston, MA: Springer US, 1990. http://dx.doi.org/10.1007/978-1-4899-0870-4_17.
Full textConference papers on the topic "Sensitivity indices"
Todorov, Venelin, and Slavi Georgiev. "An Optimization Technique for Estimating Sobol Sensitivity Indices." In 17th Conference on Computer Science and Intelligence Systems. PTI, 2022. http://dx.doi.org/10.15439/2022f170.
Full textAlgarni, Ayed A. S., and Kankar Bhattacharya. "Novel sensitivity indices based siting of distributed generation resources." In Energy Society General Meeting. IEEE, 2008. http://dx.doi.org/10.1109/pes.2008.4596504.
Full textDold, Edward J., and Philip A. Voglewede. "Sensitivity Study With Sobol’ Indices in Planar Multistable Mechanisms." In ASME 2022 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/detc2022-89414.
Full textBenidris, Mohammed, and Joydeep Mitra. "Sensitivity analysis of power system reliability indices under emission constraints." In 2014 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS). IEEE, 2014. http://dx.doi.org/10.1109/pmaps.2014.6960650.
Full textKala, Zdeněk. "Variance-based sensitivity indices for stochastic models with correlated inputs." In PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON NUMERICAL ANALYSIS AND APPLIED MATHEMATICS 2014 (ICNAAM-2014). AIP Publishing LLC, 2015. http://dx.doi.org/10.1063/1.4913077.
Full textKucherenko, Sergei, and Shufang Song. "COMPARISON OF DIFFERENT NUMERICAL ESTIMATORS FOR MAIN EFFECT GLOBAL SENSITIVITY INDICES." In 1st International Conference on Uncertainty Quantification in Computational Sciences and Engineering. Athens: Institute of Structural Analysis and Antiseismic Research School of Civil Engineering National Technical University of Athens (NTUA) Greece, 2015. http://dx.doi.org/10.7712/120215.4296.648.
Full textRaghavan, Srini H., and Michelle M. Ardeshiri. "Sensitivity analysis of measurement of modulation indices in phase modulated signals." In 2018 IEEE Aerospace Conference. IEEE, 2018. http://dx.doi.org/10.1109/aero.2018.8396646.
Full textRaghavan, Srini H., and Michelle M. Ardeshiri. "Measurement Sensitivity of Modulation Indices in Telemetry, Tracking and Command Systems." In 2019 IEEE Aerospace Conference. IEEE, 2019. http://dx.doi.org/10.1109/aero.2019.8741863.
Full textNiewiadomski, Karol, Angel Pena-Quintal, David W. P. Thomas, and Sharmila Sumsurooah. "Sensitivity Analysis of Parasitics in Power Electronic Circuit through Sobol’ Indices." In 2021 Asia-Pacific International Symposium on Electromagnetic Compatibility (APEMC). IEEE, 2021. http://dx.doi.org/10.1109/apemc49932.2021.9597088.
Full textYue, Jianpeng, Jaime A. Camelio, and Melida Chin. "Product Oriented Sensitivity Analysis for Multi-Station Compliant Assemblies." In ASME 2006 International Manufacturing Science and Engineering Conference. ASMEDC, 2006. http://dx.doi.org/10.1115/msec2006-21077.
Full textReports on the topic "Sensitivity indices"
Canavan, G. H. Sensitivity of stability indices to dealerting. Office of Scientific and Technical Information (OSTI), March 1998. http://dx.doi.org/10.2172/663410.
Full textCanavan, G. H. Sensitivity of stability indices to force uncertainties. Office of Scientific and Technical Information (OSTI), July 1997. http://dx.doi.org/10.2172/544701.
Full textBeauchemin, M., D. Pan, and K. B. Fung. Sensitivity of Landscape Indices to Classification Accuracy. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2001. http://dx.doi.org/10.4095/219782.
Full textManson, G. K., N. J. Couture, and T. S. James. CanCoast 2.0: data and indices to describe the sensitivity of Canada's marine coasts to changing climate. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2019. http://dx.doi.org/10.4095/314669.
Full textGamboa-Estrada, Fredy, and Andrés Sánchez-Jabba. The Effects of Foreign Investor Composition on Colombia´s Sovereign Debt Flows. Banco de la República Colombia, December 2022. http://dx.doi.org/10.32468/be.1222.
Full textDaudelin, Francois, Lina Taing, Lucy Chen, Claudia Abreu Lopes, Adeniyi Francis Fagbamigbe, and Hamid Mehmood. Mapping WASH-related disease risk: A review of risk concepts and methods. United Nations University Institute for Water, Environment and Health, December 2021. http://dx.doi.org/10.53328/uxuo4751.
Full textHamill, Daniel D., Jeremy J. Giovando, Chandler S. Engel, Travis A. Dahl, and Michael D. Bartles. Application of a Radiation-Derived Temperature Index Model to the Willow Creek Watershed in Idaho, USA. U.S. Army Engineer Research and Development Center, August 2021. http://dx.doi.org/10.21079/11681/41360.
Full textFluhr, Robert, and Maor Bar-Peled. Novel Lectin Controls Wound-responses in Arabidopsis. United States Department of Agriculture, January 2012. http://dx.doi.org/10.32747/2012.7697123.bard.
Full textOhad, Itzhak, and Himadri Pakrasi. Role of Cytochrome B559 in Photoinhibition. United States Department of Agriculture, December 1995. http://dx.doi.org/10.32747/1995.7613031.bard.
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