Reşat Kasap
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引用次数: 0

摘要

加拿大猞猁的数据在文献中被广泛使用和建模。虽然目前已经建立了许多不同的模型,但还没有针对残差进行基于模型的分类研究,以探讨这些模型之间的异同。这项研究回顾了先前获得的加拿大猞猁时间序列模型。本研究的出发点是残差,并使用了一些统计数据分析工具。用k均值聚类方法对模型的残差序列进行聚类。此外,本文还针对该时间序列提出了一个新的模型,并将该模型与文献中的其他模型一起纳入数据分析。此外,对各模型的残差时间序列进行混沌分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Klasik Kanada Lynx Verileri İçin Önceden Bulunmuş Zaman Serisi Modellerinin K-Means Küme Yöntemi ve BDS Testi ile İncelenmesi
Canadian lynx data are widely used and modeled in the literature. Although many different models have been made so far, no model-based classification studies have been carried out in terms of residuals to investigate the similarities or differences between these models. This study reviewed previously obtained models for the Canadian lynx time series. The starting point of the current study is residuals, and some statistical data analysis tools are used for this. The residual series of the models are clustered with the K-means cluster method. Besides, a new model is proposed for this time series, and the model is included in the data analysis together with other models in the literature. In addition, chaos analysis was performed for all residual time series of the models.
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