Assessing the Reliability of Complex Models Mathematical and Statistical Foundations of Verification, Validation, and Uncertainty Quantification (2012) / Chapter Skim
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Appendix A: Glossary
Appendix A: Glossary
Pages 109-119
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from The adjoint map is important for an input vector space to an output vector determining properties of the original space, the adjoint is an associated map map when the input and output vectors between the vector space of linear real- cannot be observed directly. It plays a valued functions on the output space to fundamental role in the theory of maps, the vector space of linear real-valued e.g., for determining solvability of inverse functions on the input space.
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These summaries are typically produced by means of numerical approximation or sampling methods such as Markov chain Monte Carlo. code verification The process of determining and See also verification, solution verification.
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continuous random variable A random variable, X, is continuous if it See also cumulative distribution function, has an absolutely continuous cumulative probability density function. distribution function.d cumulative distribution function The probability that a random variable The cdf always exists for any random Synonyms: cumulative distribution, cdf, X will be less than or equal to a value x; variable; it is monotonic nondecreasing in x, and (being a probability 0 ≤ P{X ≤ x} distribution function written as P{X ≤ x}.f,g ≤ 1.
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The most common methods of parameter estimation are "maximum likelihood" and the method of moments. Under the Bayesian approach estimates can be produced by taking the mean, median, or most likely value determined by the posterior distribution.
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The term global ensures that the analysis considers more than just local or one-factor-at-a-time effects. Hence interactions and nonlinearities are important components of a global statistical sensitivity analysis.
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model discrepancy A term accounting for or describing the In some cases, model discrepancy is the difference between a model of the system dominant source of uncertainty in modelSynonyms: model inadequacy, structural error and the true physical system. based predictions.
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.n nonintrusive methods Methods to carry out sensitivity analysis (black box methods) or forward propagation or to solve the inverse problem that only require forward runs of the computational model, effectively treating the model as a black box.
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a confidence interval, or possibly some other representation. prior probability Bayesian approach updates this prior Probability distribution assigned to Synonym: a priori probability parameters (and possibly other random probability distribution by conditioning See also Bayesian approach, posterior quantities)
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A response surface is typically estimated computationally demanding analyses (e.g., sensitivity analysis, forward from an ensemble of model runs using a propagation, solving the inverse regression, Gaussian process modeling, problem)
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subjective probability Expert judgment about uncertain events See also probability elicitation. or quantities, in the form of probability statements about future events.
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1991. Multivariate Adaptive Regression Splines.
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