Sensitivity analysis is the study of how the uncertainty in the output of a mathematical model or system (numerical or otherwise) can be divided and allocated...

Sensitivity analysis studies the relation between the uncertainty in a model-based the inference[clarify] and the uncertainties in the model assumptions...

Variance-based sensitivity analysis (often referred to as the Sobol’ method or Sobol’ indices, after Ilya M. Sobol’) is a form of global sensitivity analysis. Working...

Sensitivity analysis studies the relationship between the output of a model and its input variables or assumptions. Historically, the need for a role of...

sensitively, sensitiveness, sensitivities, or sensitivity in Wiktionary, the free dictionary. Sensitivity may refer to: Sensitivity (physiology), the ability...

Sensitivity analysis can be usefully applied to business problem, allowing the identification of those variables which may influence a business decision...

optiSLang is a software platform for CAE-based sensitivity analysis, multi-disciplinary optimization (MDO) and robustness evaluation. It was originally...

used. For more on this topic, see statistical model validation. Sensitivity analysis. A procedure to study the behavior of a system or model when global...

inputs to the filter are incorrect. Thus, the sensitivity analysis describes the robustness (or sensitivity) of the estimator to misspecified statistical...

Sensitivity analysis identifies how uncertainties in input parameters affect important measures of building performance, such as cost, indoor thermal comfort...

In statistics, robust Bayesian analysis, also called Bayesian sensitivity analysis, is a type of sensitivity analysis applied to the outcome from Bayesian...

Dominic C. (2016), MIT Critical Data (ed.), "Sensitivity Analysis and Model Validation", Secondary Analysis of Electronic Health Records, Cham: Springer...

consideration. Perform sensitivity analysis. Adopt the recommended course of action. In United States regulatory policy, cost-benefit analysis is governed by...

Sensitivity auditing is an extension of sensitivity analysis for use in policy-relevant modelling studies. Its use is recommended - i.a. in the European...

In medicine and statistics, sensitivity and specificity mathematically describe the accuracy of a test that reports the presence or absence of a medical...

robustness to failure under severe uncertainty, in particular applying sensitivity analysis of the stability radius type to perturbations in the value of a given...

in the data Scale analysis (statistics) – methods to analyse survey data by scoring responses on a numeric scale Sensitivity analysis – the study of how...

Sensitivity analysis has important applications in model calibration. One application of sensitivity analysis addresses the question of "What's important...

possibilities before the experiment is conducted. This is a form of sensitivity analysis. The idea is to estimate the difference, or fractional change, in...

1961 Werbos, Paul (1982). "Applications of advances in nonlinear sensitivity analysis" (PDF). System modeling and optimization. Springer. pp. 762–770....

hyperparameter, particularly in the method of conjugate priors, or for sensitivity analysis. When using a conjugate prior, the posterior distribution will be...

regression analysis and spatial trend, then focused on the topic of MAUP in the context of spatial epidemiology. A method of MAUP sensitivity analysis is presented...

traditional decision analysis cycle consists of four phases: basis development deterministic sensitivity analysis probabilistic analysis basis appraisal....

In applied statistics, the Morris method for global sensitivity analysis is a so-called one-factor-at-a-time method, meaning that in each run only one...

sources of uncertainty in model input and design. A related field is sensitivity analysis. A calibrated parameter does not necessarily represent reality, as...

and benefits resulting in a set of solutions that can be used for sensitivity analysis and tested in different scenarios. But there is no single optimal...

coherent form, using visualization tools such as tornado diagrams and sensitivity analysis graphs. At present, TEA is most commonly used to analyze technologies...

complete tornado. Tornado diagrams are useful for deterministic sensitivity analysis – comparing the relative importance of variables. For each variable/uncertainty...

petrochemicals and biopolymers for instance. Therefore, conducting sensitivity analysis in LCA are important to determine which parameters considerably impact...

The Eikos Sensitivity Analysis toolbox supports state of the art sensitivity analysis methods (local as well as global). Sensitivity analysis (SA) is used...