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Titlebook: Behavioral Predictive Modeling in Economics; Songsak Sriboonchitta,Vladik Kreinovich,Woraphon Y Book 2021 The Editor(s) (if applicable) an

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發(fā)表于 2025-3-21 16:49:08 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Behavioral Predictive Modeling in Economics
影響因子2023Songsak Sriboonchitta,Vladik Kreinovich,Woraphon Y
視頻videohttp://file.papertrans.cn/183/182883/182883.mp4
發(fā)行地址Presents a state-of-the-art overview of what can be done and what should be done to incorporate behavioral predictive models into econometrics.Showcases recently developed behavioral models.Written by
學(xué)科分類Studies in Computational Intelligence
圖書封面Titlebook: Behavioral Predictive Modeling in Economics;  Songsak Sriboonchitta,Vladik Kreinovich,Woraphon Y Book 2021 The Editor(s) (if applicable) an
影響因子This book presents both methodological papers on and examples of applying behavioral predictive models to specific economic problems, with a focus on how to take into account people‘s behavior when making economic predictions. This is an important issue, since traditional economic models assumed that people make wise economic decisions based on a detailed rational analysis of all the relevant aspects. However, in reality – as Nobel Prize-winning research has shown – people have a limited ability to process information and, as a result, their decisions are not always optimal. Discussing the need for prediction-oriented statistical techniques, since many statistical methods currently used in economics focus more on model fitting and do not always lead to good predictions, the book is a valuable resource for researchers and students interested in the latest results and challenges and for practitioners wanting to learn how to use state-of-the-art techniques.?.
Pindex Book 2021
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PD-Implied Ratings via Referencing a Credit Rating/Scoring Pool’s Default Experiencecally rigorous and operationally superior and granular credit risk measures such as probability of default (PD). This paper reverse-engineers a mapping methodology converting PDs to letter ratings by referencing the realized default rates of different rating categories experienced by a commercial ra
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Why Beta Priors: Invariance-Based Explanationd. The fact that there have been many successful applications of this idea seems to indicate that there must be a fundamental reason for selecting this particular family of distributions. In this paper, we show that the selection of this family can indeed be explained if we make reasonable invarianc
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Ranking-Based Voting Revisited: Maximum Entropy Approach Leads to Borda Count (and Its Versions) from each participant, a full information about his/her preferences, but such elicitation is usually too time-consuming to be practical. Instead, we only elicit, from each participant, his/her ranking of different alternatives. One of the semi-heuristic methods for decision making under such inform
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