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...

cases, variance-based measures are more appropriate. Multiple or functional outputs: Generally introduced for single-output codes, sensitivity analysis extends...

"'Explained variance' explains nothing."[page needed]: 183  Analysis of variance Variance reduction Variance-based sensitivity analysis Kent, J. T. (1983)...

by uniform distributions without variable interactions, variance based sensitivity analysis quantifies the contribution of the optimization variables...

orthogonal coordinate system that optimally describes variance in a single dataset. Robust and L1-norm-based variants of standard PCA have also been proposed...

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

Global Sensitivity Analysis. The Primer by Andrea Saltelli and other practitioners is an introduction to sensitivity analysis of model output, a discipline...

inherent sensitivity of the function to small perturbations in its input and is independent of the implementation used to solve the problem. The analysis of...

amplitude sensitivity testing (FAST) is a variance-based global sensitivity analysis method. The sensitivity value is defined based on conditional variances which...

outputs (underfitting). The variance is an error from sensitivity to small fluctuations in the training set. High variance may result from an algorithm...

global sensitivity analysis and total sensitivity indices, helping to popularize the variance-based sensitivity analysis work of the Russian mathematician...

computation of PCE-based sensitivity indices. Similar results can be obtained for Kriging. Surrogate model Variance-based sensitivity analysis Karhunen–Loève...

have to be taken into account. An alternative estimator used in a sensitivity analysis might assume that people, who were not followed for their vital status...

Discriminant function analysis ANCOVA MANOVA [1] Statsoft Textbook, ANOVA/MANOVA. [2] French, A. et al., 2010. Multivariate analysis of variance (MANOVA). [3]...

Experimental uncertainty analysis is a technique that analyses a derived quantity, based on the uncertainties in the experimentally measured quantities...

Modern portfolio theory (MPT), or mean-variance analysis, is a mathematical framework for assembling a portfolio of assets such that the expected return...

Component Analysis by Aapo Hyvärinen, Juha Karhunen, and Erkki Oja This approximation also suffers from the same problem as kurtosis (sensitivity to outliers)...

This is an inherent property of variance testing. Determining multicollinearity is useful in sensitivity analysis because the elimination of highly...

of inputs, where the costs of estimating other sensitivity analysis measures such as the variance-based measures is not affordable. Like all screening...

selected based on their content validity, unidimensionality, the degree of specificity in which a dimension is to be measured, and their amount of variance. Items...

Zhang, Jun; Mueller, Shane T. (2005). "A note on ROC analysis and non-parametric estimate of sensitivity". Psychometrika. 70: 203–212. CiteSeerX 10.1.1.162...

As such, this statistical approach involves extracting effect sizes and variance measures from various studies. By combining these effect sizes the statistical...

to sensitivity analysis include the development of the variance-based sensitivity indices which bear his name (Sobol’ indices ) and Derivative-based Global...

F.; Cariboni, J.; Saltelli, A. (2003). "Sensitivity analysis: the Morris method versus the variance based measures" (PDF). Morris, M.D. (1991). "Factorial...

method used for data analysis. Among the many such methods, some are: Analysis of variance (ANOVA) – a collection of statistical models and their associated...

software Analysis of categorical data Analysis of covariance Analysis of molecular variance Analysis of rhythmic variance Analysis of variance Analytic...

{\displaystyle r_{xy}} by substituting estimates of the covariances and variances based on a sample into the formula above. Given paired data { ( x 1 , y 1...

superposition of the contributing visual opsins. Variance in the position of the individual opsin spectral sensitivity functions therefore affects the luminous...

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

input variables for decomposition. One can use sensitivity indices (see variance-based sensitivity analysis) to define the most influential variables for...