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Everything about Probability bounds analysis
Mathematical method of risk analysis
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. For instance, it computes sure bounds on the distribution of a sum, product, or more complex function, given only sure bounds on the distributions of the inputs. Such bounds are called probability boxes, and constrain cumulative probability distributions. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Probability bounds analysisA 5-minute orientation
- Skim a recent paper: An application of fault tree analysis for computing the bounds on system failure probability through qualitative data in intuitionistic fuzzy environmentInfluential work since 2022
- Pick up a classic book: The Riemann, Lebesgue and Generalized Riemann IntegralsThe most-reprinted book on the subject
- Read the landmark paper: Uncertainty Analysis Based on Probability Bounds (P‐Box) Approach in Probabilistic Safety AssessmentCited 111 times
- Go sideways: Probability boxA closely related topic
- Go sideways: Applications of p-boxes and probability bounds analysisA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🏆 Landmark papers (most cited)
Uncertainty Analysis Based on Probability Bounds (P‐Box) Approach in Probabilistic Safety Assessment
Estimating global arthropod species richness: refining probabilistic models using probability bounds analysis
Probability bounds analysis for nonlinear dynamic process models
Probability Bounds Analysis Applied to the Sandia Verification and Validation Challenge Problem
Hard Bounds on the Probability of Performance With Application to Circuit Analysis
Probability bounds analysis for Python
Probability bounds analysis for nonlinear population ecology models
Bounds on the Prior Probability of a Set and Robust Bayesian Analysis
🆕 Influential since 2022
An application of fault tree analysis for computing the bounds on system failure probability through qualitative data in intuitionistic fuzzy environment
New upper bounds on the Gaussian Q ‐function via Jensen's inequality and integration by parts, and applications in symbol error probability analysis
📚 Books worth reading
The Riemann, Lebesgue and Generalized Riemann IntegralsA. G. Das · 2008
Entropy and the quantum IIArizona School of Analysis with Applications (2nd 2010 University of Arizona) · 2011
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
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