具有外生变量部分线性自回归模型的异方差检验的开题报告.docx

具有外生变量部分线性自回归模型的异方差检验的开题报告 【摘要】 外生变量部分线性自回归模型（Exogenous variable partial linear autoregressive model，EV-PLAR）是结合外生变量与自回归项建立的一种回归分析模型。本文旨在对该模型中异方差性的检验方法进行研究，并提出一套检验流程。 首先，本文介绍了EV-PLAR模型的基本构建及异方差的概念。然后，本文详细阐述了三种常见的异方差检验方法：Whites异方差检验、Breusch-Pagan异方差检验和Goldfeld-Quandt异方差检验。针对每种检验方法，本文分别描述其检验原理、实现步骤及分析结果的解释方法。 最后，本文结合实例进行了EV-PLAR模型中异方差检验的应用过程，并对检验结果进行了详细的分析。同时，本文还探讨了异方差性对EV-PLAR模型的影响及相应的应对措施。 通过本文的研究，我们可以为使用EV-PLAR模型进行数据回归分析的研究者提供一套完整的异方差检验流程，进而提高其研究成果的可靠性和可解释性。 【关键词】外生变量部分线性自回归模型；异方差检验；Whites 异方差检验；Breusch-Pagan 异方差检验；Goldfeld-Quandt 异方差检验；数据回归分析；可靠性；可解释性 【Abstract】 The exogenous variable partial linear autoregressive model (EV-PLAR) is a regression analysis model that combines exogenous variables with autoregressive terms. This paper aims to study the method of heteroscedasticity testing in this model and propose a set of testing procedures. Firstly, this paper introduces the basic construction of the EV-PLAR model and the concept of heteroscedasticity. Then, this paper elaborates on three common heteroscedasticity testing methods: Whites test, Breusch-Pagans test, and Goldfeld-Quandts test. For each testing method, this paper respectively describes its testing principle, implementation steps and analysis result interpretation method. Finally, this paper applies the heteroscedasticity testing process in the EV-PLAR model with an example and analyzes the test result in detail. At the same time, this paper explores the impact of heteroscedasticity on the EV-PLAR model and corresponding countermeasures. Through this study, we can provide a complete heteroscedasticity testing procedure for researchers using the EV-PLAR model for data regression analysis, thus improving the reliability and interpretability of their research results. 【Keywords】Exogenous variable partial linear autoregressive model; Heteroscedasticity testing; Whites test; Breusch-Pagans test; Goldfeld-Quandts test; Data regression analysis; Reliability; Interpretability