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  2. Uncertainty quantification - Wikipedia

    en.wikipedia.org/wiki/Uncertainty_quantification

    There are two major types of problems in uncertainty quantification: one is the forward propagation of uncertainty (where the various sources of uncertainty are propagated through the model to predict the overall uncertainty in the system response) and the other is the inverse assessment of model uncertainty and parameter uncertainty (where the ...

  3. Experimental uncertainty analysis - Wikipedia

    en.wikipedia.org/wiki/Experimental_uncertainty...

    To illustrate, a simple example of this process is to find the mean and variance of the derived quantity z = x 2 where the measured quantity x is Normally distributed with mean μ and variance σ 2. The derived quantity z will have some new PDF, that can (sometimes) be found using the rules of probability calculus. [ 7 ]

  4. Model risk - Wikipedia

    en.wikipedia.org/wiki/Model_risk

    Uncertainty on correlation parameters is another important source of model risk. Cont and Deguest propose a method for computing model risk exposures in multi-asset equity derivatives and show that options which depend on the worst or best performances in a basket (so called rainbow option) are more exposed to model uncertainty than index options.

  5. Quantification of margins and uncertainties - Wikipedia

    en.wikipedia.org/wiki/Quantification_of_margins...

    Quantification of Margins and Uncertainty (QMU) is a decision support methodology for complex technical decisions. QMU focuses on the identification, characterization, and analysis of performance thresholds and their associated margins for engineering systems that are evaluated under conditions of uncertainty, particularly when portions of those results are generated using computational ...

  6. Uncertainty analysis - Wikipedia

    en.wikipedia.org/wiki/Uncertainty_analysis

    In physical experiments uncertainty analysis, or experimental uncertainty assessment, deals with assessing the uncertainty in a measurement.An experiment designed to determine an effect, demonstrate a law, or estimate the numerical value of a physical variable will be affected by errors due to instrumentation, methodology, presence of confounding effects and so on.

  7. Monte Carlo method - Wikipedia

    en.wikipedia.org/wiki/Monte_Carlo_method

    They can also be used to model phenomena with significant uncertainty in inputs, such as calculating the risk of a nuclear power plant failure. Monte Carlo methods are often implemented using computer simulations, and they can provide approximate solutions to problems that are otherwise intractable or too complex to analyze mathematically.

  8. Investigation into deadly midair collision focuses on ...

    www.aol.com/news/investigation-deadly-midair...

    The Army said O’Hara is believed to be dead, pending positive identification of his body, and that the remains of the two other soldiers have not yet been recovered.

  9. Ensemble forecasting - Wikipedia

    en.wikipedia.org/wiki/Ensemble_forecasting

    Model uncertainty arises due to the limitations of the forecast model. The process of representing the atmosphere in a computer model involves many simplifications such as the development of parametrisation schemes, which introduce errors into the forecast. Several techniques to represent model uncertainty have been proposed.