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Title: | 非平穩性時間數列預測 Forecasting for nonstationary time series a neural networks approach |
Authors: | 于健 YU, JIAN |
Contributors: | 吳柏林 于健 YU, JIAN |
Keywords: | ARMA models, non-stationarity, model-free, neural networks, back-propagation. |
Date: | 1992 1991 |
Issue Date: | 2016-05-02 15:17:05 (UTC+8) |
Abstract: | Conventional time series analysis depends heavily on the twin assumptions of linearity and stationarity. However; there are certain cases where sampled data tend to violate the assumptions. In this paper, we use neural networks technology to explore the situation when the assumptions of linearity and stationarity are failed. At the end of the paper, we discuss an illustrative example about the annual expenditures of government and science-education-culture of R.O.C. |
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Description: | 碩士 國立政治大學 統計學系 |
Source URI: | http://thesis.lib.nccu.edu.tw/record/#B2002004642 |
Data Type: | thesis |
Appears in Collections: | [統計學系] 學位論文
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