未来ABC

IF 1.7 3区 数学 Q1 STATISTICS & PROBABILITY International Statistical Review Pub Date : 2022-10-17 DOI:10.1111/insr.12522
Henri Pesonen, Umberto Simola, Alvaro Köhn-Luque, Henri Vuollekoski, Xiaoran Lai, Arnoldo Frigessi, Samuel Kaski, David T. Frazier, Worapree Maneesoonthorn, Gael M. Martin, Jukka Corander
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引用次数: 5

摘要

近二十年来,近似贝叶斯计算(ABC)已经从一个开创性的想法发展成为基于模拟器的统计模型的实用推理工具,在许多研究领域越来越受欢迎。最近,通过采用机器学习技术来建立近似似然或后验的代理模型,以及引入具有几个高级功能的通用软件平台,包括自动并行化,提高了ABC在实际应用中的计算可行性。在这里,我们通过超越典型的基准示例,并考虑天文学、传染病流行病学、个性化癌症治疗和财务预测方面的实际应用,展示了ABC进步的优势。我们预计,ABC在现实世界中产生实际附加值和定量见解方面的新成功将继续激励科学、社会科学和技术不同领域的大量进一步应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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ABC of the future

Approximate Bayesian computation (ABC) has advanced in two decades from a seminal idea to a practically applicable inference tool for simulator-based statistical models, which are becoming increasingly popular in many research domains. The computational feasibility of ABC for practical applications has been recently boosted by adopting techniques from machine learning to build surrogate models for the approximate likelihood or posterior and by the introduction of a general-purpose software platform with several advanced features, including automated parallelisation. Here we demonstrate the strengths of the advances in ABC by going beyond the typical benchmark examples and considering real applications in astronomy, infectious disease epidemiology, personalised cancer therapy and financial prediction. We anticipate that the emerging success of ABC in producing actual added value and quantitative insights in the real world will continue to inspire a plethora of further applications across different fields of science, social science and technology.

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来源期刊
International Statistical Review
International Statistical Review 数学-统计学与概率论
CiteScore
4.30
自引率
5.00%
发文量
52
审稿时长
>12 weeks
期刊介绍: International Statistical Review is the flagship journal of the International Statistical Institute (ISI) and of its family of Associations. It publishes papers of broad and general interest in statistics and probability. The term Review is to be interpreted broadly. The types of papers that are suitable for publication include (but are not limited to) the following: reviews/surveys of significant developments in theory, methodology, statistical computing and graphics, statistical education, and application areas; tutorials on important topics; expository papers on emerging areas of research or application; papers describing new developments and/or challenges in relevant areas; papers addressing foundational issues; papers on the history of statistics and probability; white papers on topics of importance to the profession or society; and historical assessment of seminal papers in the field and their impact.
期刊最新文献
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