多样性(控制论)
阈值模型
复制
自回归模型
计量经济学
动力学(音乐)
系列(地层学)
计算机科学
线性模型
统计物理学
经济
数学
心理学
人工智能
统计
机器学习
物理
古生物学
生物
教育学
作者
Hannah Paul,Andrew Philips
摘要
Abstract Objectives Despite the frequent use of time series models in the social sciences, they have often remained within the confines of assuming purely linear dynamic effects. We contend that many theories involve relationships that are inherently non‐linear. Methods We discuss several approaches to modeling a variety of these types of non‐linear autoregressive data‐generating processes, specifically threshold effects. Results We replicate and extend a recent analysis, and show evidence of threshold processes. Conclusion In doing so, we show that threshold models allow us to test richer, more complex theoretical implications about dynamic effects.
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