使用时间序列成分断裂法 (BFTSC) 预测结构变化 (SC) 下的澳大利亚国内生产总值 (GDP)

Ajare Emmanuel Oloruntoba, Adefabi Adekunle, Adeyemo Abiodun
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引用次数: 0

摘要

这项研究的目的是让我们了解如何利用 BFTSC(时间序列成分断裂)来识别澳大利亚国内生产总值中存在的结构变化和时间序列成分。数据(澳大利亚国内生产总值)的统计时间跨度为 55 年。澳大利亚的国内生产总值是从马来西亚大学图书馆的 StreamData 中获得的高级信息。 BFAST 在结构变革方面的优势被提升为 BFTSC。BFTSC 是在对 BFAST 进行基础研究的基础上创建的,其结果显示了一种创新技术,该技术可捕捉到原始 BFAST 技术中未包含的经常性(周期性)和非经常性周期性(不规则)成分,并将其纳入了本研究的方法中。BFTSC 的创建是为了给出所有所需时间序列成分的相互图像。随后确定了预测技术并进行了预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Forecasting Australia Gross Domestic Product (GDP) under Structural Change (SC) Using Break for Time Series Components (BFTSC)
The reason for this research is to enable us know the use BFTSC (break for time series components) in identification of the structural change and the time series components  existing in Australia GDP. The data (Australia GDP) statistics spanned for period of fifty five years. The GDP of Australia is a higher information gotten from the StreamData of Universiti Utara Malaysia Library.  The precincts of BFAST in terms of structural change was advanced to become  BFTSC. BFTSC was created from basic research conducted on BFAST, results shows an innovative technique that captures the recurring (cyclicals) and non-recurring cyclical (irregular) components that was not included in the original BFAST technique and it was included in the methodology of this study. BFTSC was created to give a mutual image of all the required time series components. The subsequently forecasting technique was determined and forecast is made.
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