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Using Preferred Outcome Distributions to Estimate Value and Probability Weighting Functions in Decisions under Risk [PDF]
, 2013 In this paper we propose the use of preferred outcome distributions as a new method to elicit individuals’ value and probability weighting functions in decisions under risk.
Dellaert, B.G.C. (Benedict) +3 more
core +10 more sources
Alexandria Engineering Journal, 2023 Probabilistic dual hesitant fuzzy set (PDHFS) can better reflect the hesitant attitude and probability information of decision-makers than existing fuzzy sets.
Baoquan Ning +3 more
doaj +1 more source
Lubricants, 2022 Information such as probability distribution, performance degradation trajectory, and performance reliability function varies with the service status of rolling bearings, which is difficult to analyze and evaluate using traditional reliability theory ...
Liang Ye +5 more
doaj +1 more source
Technological and Economic Development of Economy, 2023 Probabilistic dual hesitant fuzzy set (PDHFS) is a more powerful and important tool to describe uncertain information regarded as generalization of hesitant fuzzy set (HFS) and dual HFS (DHFS), not only reflects the hesitant attitude of decision-makers (
Baoquan Ning +3 more
doaj +1 more source
Probability weighting and insurance demand in a unified framework
The Geneva Risk and Insurance Review, 2022 We provide a comprehensive analysis of the impact of probability weighting on optimal insurance demand in a unified framework. We identify decreasing relative overweighting as a new local condition on the probability weighting function that is useful for
J. Jaspersen, R. Peter, Marc A. Ragin
semanticscholar +1 more source
A shocking experiment: New evidence on probability weighting and common ratio violations
Judgment and Decision Making, 2007 We study whether probability weighting is observed when individuals are presented with a series of choices between lotteries consisting of real non-monetary adverse outcomes, electric shocks.
Gregory S. Berns +3 more
doaj +1 more source
Second-best probability weighting
Games Econ. Behav., 2022 Non-linear probability weighting is an integral part of descriptive theories of choice under risk such as prospect theory. But why do these objective errors in information processing exist?
Florian Herold, N. Netzer
semanticscholar +1 more source
A Decision Probability Transformation Method Based on the Neural Network
Entropy, 2022 When the Dempster–Shafer evidence theory is applied to the field of information fusion, how to reasonably transform the basic probability assignment (BPA) into probability to improve decision-making efficiency has been a key challenge.
Junwei Li, Aoxiang Zhao, Huanyu Liu
doaj +1 more source
The Slicing Method: Determining Insensitivity Regions of Probability Weighting Functions
Computational Economics, 2021 A popular rule of thumb, usually called "heuristic technique" in Behavioral Economics, for determining the likelihood insensitivity regions of probability weighting functions (pwf's) is based on searching for points at which the pwf's are twice their values at half the points.
Egozcue, Martin +2 more
openaire +3 more sources
Nonlinear Probability Weighting Can Reflect Attentional Biases in Sequential Sampling
Annual Meeting of the Cognitive Science Society, 2021 Nonlinear probability weighting allows cumulative prospect theory (CPT) to account for key phenomena in decision making under risk (e.g., certainty effect, fourfold pattern of risk attitudes).
Veronika Zilker, Thorsten Pachur
semanticscholar +1 more source