A Projection-Based Diagnostic Test for Generalized Functional Regression Models

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2024-01-01 DOI:10.5705/ss.202022.0083

Guizhen Li, Mengying You, Lingzhi Zhou, Hua Liang, Huazhen Lin

引用次数: 0

Abstract

A Projection-Based Diagnostic Test for Generalized Functional Regression Models

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基于投影的广义功能回归模型诊断测试

我们提出了一种新的诊断检验来检查广义函数回归模型的拟合优度。建议的测试不需要对分布进行说明，并且可以应用于常用的函数回归模型。因为它是基于分布的独立性，所以它包括了基于均值和基于高阶矩的检验作为特例。特别地，我们通过沿一定方向投射函数来克服函数数据的无限大维数的问题。此外，为了避免这些方向的主观选择造成的偏差，我们对函数变量项目的方向进行了积分。结果表明，所提出的测试方法在提高局部幂的同时，克服了无穷维问题。开发了一个简单的实现程序。通过理论和仿真研究对所提出的测试方法的性能进行了评价。我们将提出的程序应用于分析加拿大的天气数据和中国的空气污染数据，得到了几个有趣的模型，它们比现有方法具有更高的可解释性和估计精度。

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

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.