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     The Analysis of Power Demand in China Using Cointegration Model and Combination Forecasting Method
     基于协整模型与组合预测的中国电力需求分析
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     The Researching Colntegration Model of Society,Economy and Population System in Harmonious Society
     和谐社会下社会经济与人口的协整模型探索
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     The Researching Cointegration Model of Society, Economy and Population System in Harmonious Society
     和谐社会下社会经济与人口的协整模型探索
     Secondly, several common ARMA models and ARCH models are introduced in detail, and fractionally integrated models, such as ARFIMA and FIGARCH, which are developed in recent years, are introduced, too.
     然后介绍了几种常用的ARMA模型和ARCH模型,其次重点介绍了近几年刚刚发展的分整模型,即ARFIMA模型和FIGARCH模型,并对其进行比较分析,指出这些模型的不足和适用范围。
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     The application of ARFIMA model in the price forecasting of commodity
     分整模型在商品价格预测中的应用
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     Obviously, EVA model turns out a scientific appraisals to motivate the managers.
     该模型为:
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     model.
     模型
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     Fractional integrated augmented GARCH-M model
     分增广GARCH-M模型
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     Firstly, a whole vehicle dynamics model is established.
     首先建立了车动力学模型
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     N( Z ) .
     N(Z)的和(和)图.
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It is provided cointegration and error correction model in this paper. We analyze the requirement of foreign capital, and study the interactions influencing the factors such as the requirement of foreign capital and GDP, export total sum,import total sum and RE in China. The result indicates that the requirement of foreign capital exists cointegration model,and there are the two-way cause and effect relation to the requirement of foreign capital and GDP,export total sum import total Sum and RE.

应用协整与误差校正模型,对我国的外资需求进行协整与误差校正分析,研究我国外资需求与国内生产总值、出口总额、通货膨胀率等影响因素的相互作用。结果表明外资需求存在协整模型,外资需求与国民生产总值、出口总额、进口总额和汇率有双向因果关系。

To begin with the introduction of ARFIMA model, a new branch of Time Series Analysis,the paper analyzes the advantage of ARFIMA model over the traditional time series models and gives the parameter estimation method and the forecasting formula of ARFIMA model.The ARFIMA model not only reflects the long memory property of time series which cannot be reflected by traditional time series models,but also solves the problem of over parameterization which occurs when applying traditional time series models to the...

To begin with the introduction of ARFIMA model, a new branch of Time Series Analysis,the paper analyzes the advantage of ARFIMA model over the traditional time series models and gives the parameter estimation method and the forecasting formula of ARFIMA model.The ARFIMA model not only reflects the long memory property of time series which cannot be reflected by traditional time series models,but also solves the problem of over parameterization which occurs when applying traditional time series models to the price forecasting of commodity.Finally,a positive study is presented.

首先介绍了时间序列分析中的一个新领域——长记忆分整模型 (ARFIMA) ,分析了该模型与传统时间序列模型相比较所体现出的优越性 ,及其参数估计和预测方法 .本文所给出的分整模型不仅反映了传统时间序列模型所不能反映的时间序列长记忆性 ,而且解决了利用传统方法预测商品价格中的过度参数化问题 ,从而显著提高了商品价格预测的可靠性 .文章还给出了实际案例分析 .

This paper considers the generalixed method of moments ( GMM) approach of the cointegration vectors generated by no-gaussion errors, which is linear restrictions and discusses estimation、 asymptotic、 test of the cointeration vectors, and gets good results.

将Quintos研究的一类向量误差校整模型,推广到其协整向量满足某种线性限制的情形,并讨论协整向量的收敛性和 极限分布,得到了相应的结论。

 
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