多维分布的多变量标量回归应用于体育锻炼与认知功能之间关系的建模。

IF 16.4 1区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY
Rahul Ghosal, Marcos Matabuena
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引用次数: 0

摘要

我们为多维标量的多维分布回归开发了一种新方法。传统方法通常分析孤立的单变量标量结果,或将单维分布表示视为预测因子。然而,这些方法并不理想,因为 (i) 它们未能利用分布预测因子之间的依赖关系,(ii) 忽视了响应的相关结构。为了克服这些局限性,我们提出了一个多变量分布分析框架,利用多变量密度函数和多任务学习的力量。我们开发了一种计算高效的半参数估计方法,用于模拟潜在联合密度对相关多元响应的影响。此外,我们还引入了一种新的共形预测算法,用于量化基于受试者特征和个性化分布预测因子的多元预测的不确定性,从而为了解反应的条件分布提供有价值的见解。我们通过全面的数值模拟验证了我们提出的方法的有效性,清楚地证明了它与传统方法相比的优越性能。我们在 2011-2014 年全国健康与营养调查的三轴加速度计数据上演示了所提方法的应用,以模拟老年人群中不同领域的认知分数与体力活动分布表示之间的关联。我们的结果凸显了所提方法的优势,强调了在三轴加速度计数据中纳入多维分布信息的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Multivariate Scalar on Multidimensional Distribution Regression With Application to Modeling the Association Between Physical Activity and Cognitive Functions

Multivariate Scalar on Multidimensional Distribution Regression With Application to Modeling the Association Between Physical Activity and Cognitive Functions

We develop a new method for multivariate scalar on multidimensional distribution regression. Traditional approaches typically analyze isolated univariate scalar outcomes or consider unidimensional distributional representations as predictors. However, these approaches are suboptimal because (i) they fail to utilize the dependence between the distributional predictors and (ii) neglect the correlation structure of the response. To overcome these limitations, we propose a multivariate distributional analysis framework that harnesses the power of multivariate density functions and multitask learning. We develop a computationally efficient semiparametric estimation method for modeling the effect of the latent joint density on the multivariate response of interest. Additionally, we introduce a new conformal prediction algorithm for quantifying the uncertainty of our multivariate predictions based on subject characteristics and individualized distributional predictors, providing valuable insights into the conditional distribution of the response. We validate the effectiveness of our proposed method through comprehensive numerical simulations, clearly demonstrating its superior performance compared to traditional methods. The application of the proposed method is demonstrated on triaxial accelerometer data from the National Health and Nutrition Examination Survey 2011–2014 for modeling the association between cognitive scores across various domains and distributional representation of physical activity among the older adult population. Our results highlight the advantages of the proposed approach, emphasizing the significance of incorporating multidimensional distributional information in the triaxial accelerometer data.

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来源期刊
Accounts of Chemical Research
Accounts of Chemical Research 化学-化学综合
CiteScore
31.40
自引率
1.10%
发文量
312
审稿时长
2 months
期刊介绍: Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.
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