Finite approximations of data-based decision problems under imprecise probabilities
type: Item
instance of: scholarly article
title: Finite approximations of data-based decision problems under imprecise probabilities
zbMATH Open document ID: 1185.62022
published in: International Journal of Approximate Reasoning
publication date: 2010-04-07T00:00:00Z
Mathematics Subject Classification ID: 62C99
zbMATH DE Number: 5690188
zbMATH Keywords: imprecise probability
zbMATH Keywords: coherent lower prevision
zbMATH Keywords: data-based decision theory
zbMATH Keywords: discretization
author: Robert Hable
MaRDI profile type: Publication
full work available at URL: j.ijar.2009.05.003
OpenAlex ID: W1998927957
cites work: Q5800557
cites work: Statistical decision theory and Bayesian analysis. 2nd ed
cites work: Asymptotic methods in statistical decision theory
cites work: Q3999364
cites work: The theory of interval-probability as a unifying concept for uncertainty
cites work: Maxmin expected utility with non-unique prior
cites work: Decision making under uncertainty using imprecise probabilities
cites work: Direct algorithms for checking consistency and making inferences from conditional probability assessments
cites work: Optimal decisions under complex uncertainty – basic notions and a general algorithm for data‐based decision making with partial prior knowledge described by interval probability
cites work: Finite approximations to coherent choice
cites work: A survey of the theory of coherent lower previsions
cites work: Q3663565
cites work: Q3254057
cites work: Data-based decisions under imprecise probability and least favorable models
cites work: Q3628773
cites work: Q4398693
cites work: Q3703086
cites work: Minimax tests and the Neyman-Pearson lemma for capacities
DOI: 10.1016/J.IJAR.2009.05.003
Recommended article: Data-based decisions under imprecise probability and least favorable models
Recommended article: Optimal decisions under complex uncertainty – basic notions and a general algorithm for data‐based decision making with partial prior knowledge described by interval probability
Recommended article: Decision making with imprecise probabilistic information
Recommended article: Decision making under incomplete data using the imprecise Dirichlet model
Recommended article: Decision making under uncertainty using imprecise probabilities
Recommended article: Generalized probabilistic approximations of incomplete data
Recommended article: Robust Decisions under Risk for Imprecise Probabilities
Recommended article: Approximation of decision rules in stochastic programming
Recommended article: A generalization of the fundamental theorem of de Finetti for imprecise conditional probability assessments
description: scientific article; zbMATH DE number 5690188