Generalized infinite factorization models.

IF 2.4 2区 数学 Q2 BIOLOGY
Biometrika Pub Date : 2022-09-01 Epub Date: 2022-01-19 DOI:10.1093/biomet/asab056
L Schiavon, A Canale, D B Dunson
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引用次数: 14

Abstract

Factorization models express a statistical object of interest in terms of a collection of simpler objects. For example, a matrix or tensor can be expressed as a sum of rank-one components. However, in practice, it can be challenging to infer the relative impact of the different components as well as the number of components. A popular idea is to include infinitely many components having impact decreasing with the component index. This article is motivated by two limitations of existing methods: (1) lack of careful consideration of the within component sparsity structure; and (2) no accommodation for grouped variables and other non-exchangeable structures. We propose a general class of infinite factorization models that address these limitations. Theoretical support is provided, practical gains are shown in simulation studies, and an ecology application focusing on modelling bird species occurrence is discussed.

广义无限分解模型。
分解模型用一组更简单的对象来表示感兴趣的统计对象。例如,矩阵或张量可以表示为秩一分量的和。然而,在实践中,推断不同组件的相对影响以及组件的数量可能是具有挑战性的。一个流行的想法是包含无限多个分量,它们的影响随分量指数递减。现有方法的两个局限性促使了本文的研究:(1)缺乏对组件内部稀疏结构的仔细考虑;(2)不能容纳分组变量和其他不可交换结构。我们提出了一类一般的无限分解模型来解决这些限制。本文提供了理论支持,在模拟研究中取得了实际成果,并讨论了以模拟鸟类物种发生为重点的生态学应用。
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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来源期刊
Biometrika
Biometrika 生物-生物学
CiteScore
5.50
自引率
3.70%
发文量
56
审稿时长
6-12 weeks
期刊介绍: Biometrika is primarily a journal of statistics in which emphasis is placed on papers containing original theoretical contributions of direct or potential value in applications. From time to time, papers in bordering fields are also published.
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