On data-based estimation of possibility distributions

Hose Dominik; Hanss Michael

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On data-based estimation of possibility distributions

机译：关于基于数据的可能性分布估算

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摘要

In this paper, we show how a possibilistic description of uncertainty arises very naturally in statistical data analysis. In combination with recent results in inverse uncertainty propagation and the consistent aggregation of marginal possibility distributions, this estimation procedure enables a very general approach to possibilistic identification problems in the framework of imprecise probabilities, i.e. the non-parametric estimation of possibility distributions of uncertain variables from data with a clear interpretation. (C) 2020 Elsevier B.V. All rights reserved.

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来源
《Fuzzy sets and systems》 |2020年第15期|77-94|共18页
作者
Hose Dominik; Hanss Michael;
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作者单位

Univ Stuttgart Inst Engn & Computat Mech Pfaffenwaldring 9 D-70569 Stuttgart Germany;

Univ Stuttgart Inst Engn & Computat Mech Pfaffenwaldring 9 D-70569 Stuttgart Germany;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种 eng
中图分类
关键词
Possibilistic statistics; Probability-possibility consistency; Fuzzy membership estimation; Possibility distribution estimation; Fuzzy measurement equations;

机译：可能性统计;可能性一致性;模糊会员估计;可能性分布估计;模糊测量方程;

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On data-based estimation of possibility distributions

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