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Sensitivity analysis. 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 to different sources of uncertainty in its inputs. [1][2] This involves estimating sensitivity indices that quantify the influence of an input or group of inputs on ...
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. [ 1 ] [ 2 ] Working within a probabilistic framework, it decomposes the variance of the output of the model or system into fractions which can be attributed to inputs or sets of inputs.
Techno-economic assessment or techno-economic analysis (abbreviated TEA) is a method of analyzing the economic performance of an industrial process, product, or service. The methodology originates from earlier work on combining technical, economic and risk assessments for chemical production processes. [1] It typically uses software modeling to ...
The Price Sensitivity Meter (PSM) is a market technique for determining consumer price preferences. It was introduced in 1976 by Dutch economist Peter van Westendorp. The technique has been used by a wide variety of researchers in the market research industry. The PSM approach has been a staple technique for addressing pricing issues for the ...
Definition. Youden's J statistic is. with the two right-hand quantities being sensitivity and specificity. Thus the expanded formula is: The index was suggested by W. J. Youden in 1950 [1] as a way of summarising the performance of a diagnostic test; however, the formula was earlier published in Science by C. S. Pierce in 1884. [2] Its value ...
Fourier amplitude sensitivity testing (FAST) is a variance-based global sensitivity analysis method. The sensitivity value is defined based on conditional variances which indicate the individual or joint effects of the uncertain inputs on the output. FAST first represents conditional variances via coefficients from the multiple Fourier series ...
Sensitivity analysis studies the relationship between the output of a model and its input variables or assumptions. Historically, the need for a role of sensitivity analysis in modelling, and many applications of sensitivity analysis have originated from environmental science and ecology. [1]
Sensitivity analysis has important applications in model calibration. One application of sensitivity analysis addresses the question of "What's important to model or system development?" One can seek to identify important connections between observations, model inputs, and predictions or forecasts. That is, one can seek to understand what ...
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