Ambiguity Reduction Through new Statistical Data
نویسندگان
چکیده
We provide some objective foundations for a belief revision process in a situation where (i) the decision-maker's initial probabilistic knowledge is imprecise and characterized by the core of a belief function, (ii) expected new data are themselves consistent with a belief function with known focal sets and (iii) the revision process is based on belief function combination. We study the properties of the information value for such a revising in the Gilboa±Schmeidler multi-prior model. Ó 2000 Elsevier Science Inc. All rights reserved.
منابع مشابه
بررسی رابطه ابهام نقش با خشنودی شغلی و عملکرد شغلی با میانجی گری رفتارهای پویای شغلی
Abstract Introduction: Job stress such as role ambiguity, a situation that arises from the interaction between people and jobs, reduces the performance and job satisfaction. Proactive people eliminate ambiguity in their jobs by behaviors such as innovation. The present study aimed at investigating the impact of proactive person...
متن کاملA Trajectory Data Clustering Method Based On Dynamic Grid Density
Under the traditional method of frequent trajectory mining, the location of data is obtained through the GPS device. However, limited equipment accuracy may incur location ambiguity. In this paper, we propose a new trajectory data clustering method based on dynamic grid density, in order to remove this ambiguity. In this method, the trajectory space of an object is firstly divided into equal-si...
متن کاملA causal model of burnout based on health anxiety, family-work conflict, and tolerance of ambiguity in IOOC employees
This paper aims to investigate this important issue from the perspective of the effect of psychological variables such as health anxiety, family-work conflict and tolerance of ambiguity on burnout in a sampel of 502 statistical population of headquarters staff of the Iranian Offshore Oil Company in Tehran. Structural equation modeling was used to analysis using AMOS24 software.The sampe method ...
متن کاملAmbiguity reduction by objective model selection , with an application to the costs of the EU 2030 climate targets Richard
I estimate the cost of meeting the EU 2030 targets for greenhouse gas emission reduction, using statistical emulators of ten alternative models. Assuming a first-best policy implementation, I find that total and marginal costs are modest. The statistical emulators allow me to compute the risk premiums, which are small because the EU is rich and the policy impact is small. The ensemble of ten mo...
متن کاملNear-Optimal Ambiguity Sets for Distributionally Robust Optimization
We propose a novel, Bayesian framework for assessing the relative strengths of data-driven ambiguity sets in distributionally robust optimization (DRO). The key idea is to measure the relative size between a candidate ambiguity set and an asymptotically optimal set as the amount of data grows large. This asymptotically optimal set is provably the smallest convex ambiguity set that satisfies a s...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 1999