Constructing belief functions from sample data using multinomial confidence regions
From MaRDI portal
Publication:2506951
DOI10.1016/j.ijar.2006.01.001zbMath1100.68112OpenAlexW198128968MaRDI QIDQ2506951
Publication date: 10 October 2006
Published in: International Journal of Approximate Reasoning (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.ijar.2006.01.001
confidence intervalsDempster-Shafer theorytransferable belief modelevidence theorymultinomial proportions
Related Items
Active classification using belief functions and information gain maximization ⋮ Evidential calibration of binary SVM classifiers ⋮ Prediction of future observations using belief functions: a likelihood-based approach ⋮ Constructing consonant belief functions from sample data using confidence sets of pignistic probabilities ⋮ Unifying practical uncertainty representations. I. Generalized \(p\)-boxes ⋮ Dempster-Shafer approximations and probabilistic bounds in statistical matching ⋮ A Gibbs Sampler for a Class of Random Convex Polytopes ⋮ Frequency-calibrated belief functions: review and new insights ⋮ Belief functions induced by random fuzzy sets: a general framework for representing uncertain and fuzzy evidence ⋮ Toward credible belief base revision ⋮ Envelopes of equivalent martingale measures and a generalized no-arbitrage principle in a finite setting ⋮ Generation of production rules with belief functions to train fuzzy neural network in diagnostic system ⋮ Addressing ambiguity in randomized reinsurance stop-loss treaties using belief functions ⋮ Dempster-Shafer theory and statistical inference with weak beliefs ⋮ Idempotent conjunctive combination of belief functions: extending the minimum rule of possibility theory ⋮ Consonant Belief Function Induced by a Confidence Set of Pignistic Probabilities ⋮ A relationship between probability interval and random sets and its application to linear optimization with uncertainties ⋮ On indexing evidential data ⋮ Shape from silhouette using Dempster-Shafer theory ⋮ Evidential reasoning in large partially ordered sets. Application to multi-label classification, ensemble clustering and preference aggregation ⋮ Probabilistic set-membership approach for robust regression ⋮ An algebraic theory for statistical information based on the theory of hints ⋮ Defining belief functions using mathematical morphology - application to image fusion under imprecision ⋮ Calibrated model-based evidential clustering using bootstrapping ⋮ Validity, consonant plausibility measures, and Conformal prediction ⋮ Valid inferential models for prediction in supervised learning problems ⋮ Probability envelopes and their Dempster-Shafer approximations in statistical matching ⋮ Large scale two sample multinomial inferences and its applications in genome-wide association studies ⋮ Probabilistic inference for multiple testing
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Perspectives on the theory and practice of belief functions
- Inferring a possibility distribution from empirical data
- A family of simultaneous confidence intervals for multinomial proportions
- Propagating belief functions in qualitative Markov trees
- Belief function representations of statistical evidence
- A process for generating quantitative belief functions
- Resolving misunderstandings about belief functions
- Belief functions: The disjunctive rule of combination and the generalized Bayesian theorem
- The transferable belief model
- Applications of bootstrap methods for categorical data analysis.
- Towards a unified theory of imprecise probability
- Binary join trees for computing marginals in the Shenoy-Shafer architecture
- Simultaneous confidence intervals for multinomial proportions.
- A mathematical theory of hints. An approach to the Dempster-Shafer theory of evidence
- An introduction to the imprecise Dirichlet model for multinomial data
- Extensions of belief functions and possibility distributions by using the imprecise Dirichlet model
- An uncertainty interchange format with imprecise probabilities
- Belief functions on real numbers
- PROBABILITY INTERVALS: A TOOL FOR UNCERTAIN REASONING
- Belief functions and statistical inference
- Quick Simultaneous Confidence Intervals for Multinomial Proportions
- Simultaneous Confidence Intervals and Sample Size Determination for Multinomial Proportions
- Large Sample Simultaneous Confidence Intervals for Multinomial Proportions
- On Simultaneous Confidence Intervals for Multinomial Proportions
- Upper and Lower Probabilities Induced by a Multivalued Mapping
- New Methods for Reasoning Towards Posterior Distributions Based on Sample Data
- Upper and Lower Probabilities Generated by a Random Closed Interval
- A Class of Random Convex Polytopes