Reconstructing nonlinear structure in regression residuals

Michael McCullough; Thomas L Marsh; Ron C Mittelhammer

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Reconstructing nonlinear structure in regression residuals

机译：重构回归残差中的非线性结构

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摘要

Phase space reconstruction is investigated as a diagnostic tool for uncovering structure of nonlinear processes in regression residuals. Results in the form of phase portraits (e.g. scatter plots of reconstructed dynamical systems) and descriptive statistics provide information that can identify underlying structural components from stochastic data outcomes, even in cases where such data appear essentially random, and provide insights categorizing structural components into functional classes to inform econometric/time series modeling efforts. Empirical evidence supporting this approach is provided using simulations from an Ikeda mapping. An application to US hops exports is used to illustrate the application of the approach.

机译：相空间重构是一种诊断工具，用于揭示回归残差中非线性过程的结构。以相图（例如，重建的动力学系统的散点图）和描述性统计形式的结果提供了可以从随机数据结果中识别出潜在结构成分的信息，即使在此类数据看起来基本上是随机的情况下，也提供了将结构成分分类为功能的见解类，以告知计量经济/时间序列建模工作。使用池田制图的模拟提供了支持这种方法的经验证据。以美国啤酒花出口为例，说明了该方法的应用。

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来源
《Journal of applied statistics》 |2014年第2期|332-350|共19页
作者
Michael McCullough; Thomas L Marsh; Ron C Mittelhammer;
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作者单位

Agribusiness Department, California Polytechnic State University, San Luis Obispo, CA 93407, USA;

School of Economic Sciences, Washington State University, Pullman, WA, USA;

School of Economic Sciences, Washington State University, Pullman, WA, USA;

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正文语种 eng
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关键词
phase space reconstruction; recurrence quantification analysis; hops exports; information and entropy economics; residual diagnostics;

机译：相空间重构;复发定量分析;啤酒花出口;信息和熵经济学;残留诊断;

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机译：非线性回归中的残差

Reconstructing nonlinear structure in regression residuals

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