在Logistic回归中使用调查抽样算法进行精确推理

IF 1.7 3区 数学 Q1 STATISTICS & PROBABILITY
Louis-Paul Rivest, Serigne Abib Gaye
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引用次数: 1

摘要

逻辑回归的几个精确推理程序需要根据条件分布模拟0‐1相关向量,给定一些干扰参数的足够统计。在这项工作中,这被视为一个抽样问题,涉及n个单位的种群、不相等的选择概率和平衡约束。精确推理的这种重新表述的基础是一个命题,当n变为无穷大时,在给定逻辑回归充分统计量的情况下,推导出依赖向量的条件分布的极限。建议使用立方体采样算法对此分布进行采样。这种方法对精确推理的兴趣通过解决新问题来说明。首先,它允许用连续协变量进行精确推理。它也有助于研究几个0-1矢量之间的部分相关性。这在一个处理生态学中存在-不存在数据的例子中得到了说明。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using Survey Sampling Algorithms For Exact Inference in Logistic Regression

Several exact inference procedures for logistic regression require the simulation of a 0-1 dependent vector according to its conditional distribution, given the sufficient statistics for some nuisance parameters. This is viewed, in this work, as a sampling problem involving a population of n units, unequal selection probabilities and balancing constraints. The basis for this reformulation of exact inference is a proposition deriving the limit, as n goes to infinity, of the conditional distribution of the dependent vector given the logistic regression sufficient statistics. It is proposed to sample from this distribution using the cube sampling algorithm. The interest of this approach to exact inference is illustrated by tackling new problems. First it allows to carry out exact inference with continuous covariates. It is also useful for the investigation of a partial correlation between several 0-1 vectors. This is illustrated in an example dealing with presence-absence data in ecology.

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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.
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