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Probability bounds analysis (PBA) is a collection of methods of uncertainty propagation for making qualitative and quantitative calculations in the face of uncertainties of various kinds. It is used to project partial information about random variables and other quantities through mathematical expressions.
Probability bounds analysis is used to make arithmetic and logical calculations with p-boxes. An example p-box is shown in the figure at right for an uncertain number x consisting of a left (upper) bound and a right (lower) bound on the probability distribution for x. The bounds are coincident for values of x below 0 and above 24. The bounds ...
Analysis of species sensitivity distributions [3] Sensitivity analysis in aerospace engineering of the buckling load of the frontskirt of the Ariane 5 launcher [4] ODE models of chemical reactor dynamics [5] [6] Pharmacokinetic variability of inhaled VOCs [7] Groundwater modeling [8] Bounding failure probability for series systems [9]
A representative guide for obtaining informed consent from people participating in social science or behavioural research, or of the potential risks of a medical procedure, suggests giving typical numerical chances of an adverse event when words of estimative probability first are used.
Possibility theory is a mathematical theory for dealing with certain types of uncertainty and is an alternative to probability theory. It uses measures of possibility and necessity between 0 and 1, ranging from impossible to possible and unnecessary to necessary, respectively.
The observed data are statistically compared against the equivalence bounds. If the statistical test indicates the observed data is surprising, assuming that true effects are at least as extreme as the equivalence bounds, a Neyman-Pearson approach to statistical inferences can be used to reject effect sizes larger than the equivalence bounds ...
The possibility space is a framework that allows for the analysis of all possible consequences and benefits of a suitability analysis. This is created through geometrical data analysis conducted in real time with technological land mapping, allowing for the development of multiple combinations of suitability.
In order to give the definition for something that is PAC-learnable, we first have to introduce some terminology. [2] For the following definitions, two examples will be used. The first is the problem of character recognition given an array of bits encoding a binary-valued image. The other example is the problem of finding an interval that will ...