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  2. Sensitivity analysis - Wikipedia

    en.wikipedia.org/wiki/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 the output.

  3. Morris method - Wikipedia

    en.wikipedia.org/wiki/Morris_method

    A sensitivity analysis method widely used to screen factors in models of large dimensionality is the design proposed by Morris. [3] The Morris method deals efficiently with models containing hundreds of input factors without relying on strict assumptions about the model, such as for instance additivity or monotonicity of the model input-output ...

  4. Tornado diagram - Wikipedia

    en.wikipedia.org/wiki/Tornado_diagram

    Completed Tornado Diagram. Tornado diagrams, also called tornado plots, tornado charts or butterfly charts, are a special type of Bar chart, where the data categories are listed vertically instead of the standard horizontal presentation, and the categories are ordered so that the largest bar appears at the top of the chart, the second largest appears second from the top, and so on.

  5. Elementary effects method - Wikipedia

    en.wikipedia.org/wiki/Elementary_effects_method

    EE is applied to identify non-influential inputs for a computationally costly mathematical model or for a model with a large number of inputs, where the costs of estimating other sensitivity analysis measures such as the variance-based measures is not affordable. Like all screening, the EE method provides qualitative sensitivity analysis ...

  6. Variance-based sensitivity analysis - Wikipedia

    en.wikipedia.org/wiki/Variance-based_sensitivity...

    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.

  7. Receiver operating characteristic - Wikipedia

    en.wikipedia.org/wiki/Receiver_operating...

    A classification model (classifier or diagnosis [7]) is a mapping of instances between certain classes/groups.Because the classifier or diagnosis result can be an arbitrary real value (continuous output), the classifier boundary between classes must be determined by a threshold value (for instance, to determine whether a person has hypertension based on a blood pressure measure).

  8. Sensitivity and specificity - Wikipedia

    en.wikipedia.org/wiki/Sensitivity_and_specificity

    The 'worst-case' sensitivity or specificity must be calculated in order to avoid reliance on experiments with few results. For example, a particular test may easily show 100% sensitivity if tested against the gold standard four times, but a single additional test against the gold standard that gave a poor result would imply a sensitivity of ...

  9. Pointer analysis - Wikipedia

    en.wikipedia.org/wiki/Pointer_analysis

    Field sensitivity (also known as structure sensitivity): An analysis can either treat each field of a struct or object separately, or merge them. Array sensitivity: An array-sensitive pointer analysis models each index in an array separately. Other choices include modelling just the first entry separately and the rest together, or merging all ...