书目名称 | Causal Analytics for Applied Risk Analysis | 编辑 | Louis Anthony Cox Jr.,Douglas A. Popken,Richard X. | 视频video | | 概述 | Highlights causal analytics methods that answer how changing decision variables can change probabilities of various outcomes.Presents models, algorithms, principles, and software for deriving causal m | 丛书名称 | International Series in Operations Research & Management Science | 图书封面 |  | 描述 | Causal analytics methods can revolutionize the use of data to make effective decisions by revealing how different choices affect probabilities of various outcomes. This book presents and illustrates models, algorithms, principles, and software for deriving causal models from data and for using them to optimize decisions with uncertain outcomes. It discusses how to describe and summarize situations; detect changes; evaluate effects of policies or interventions; learn what works best under different conditions; predict values of as-yet unobserved quantities from available data; and identify the most likely explanations for observed outcomes, including surprises and anomalies. The book resents practical techniques for causal modeling and analytics that practitioners can apply to improve understanding of how choices affect probabilities of consequences and, based on this understanding, to recommend choices that are more likely to accomplish their intended objectives.The book begins with a survey of modern analytics methods, focusing mainly on techniques useful for decision, risk, and policy analysis. Chapter 2 introduces free in-browser software, including the Causal Analytics Toolkit | 出版日期 | Book 2018 | 关键词 | Decision Making; Risk Analysis; Risk Management; Risk Models; Causal Analytics; Risk Analytics; Descriptiv | 版次 | 1 | doi | https://doi.org/10.1007/978-3-319-78242-3 | isbn_softcover | 978-3-030-08653-4 | isbn_ebook | 978-3-319-78242-3Series ISSN 0884-8289 Series E-ISSN 2214-7934 | issn_series | 0884-8289 | copyright | Springer International Publishing AG, part of Springer Nature 2018 |
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