文档介绍：摘要
消费者信心指数在一定程度上反应了经济发展的现状,论文基于这一指数建立的平稳时间序列模型,:
首先,介绍了一种新的估计平稳时间序列模型的参数估计方法,给出了拟积分函数是积分函数到鞅变换估计空间的投影以及当核函数从可数集中选取时,变换积分函数可以逼近积分函数的证明,,针对鞅变换估计函数的优化问题提出了一种猜想.
其次,分析了消费者信心指数的时序图,通过平稳时间序列模型的识别方法,,计算出该数据的自相关和偏相关系数值,并通过SAS软件,选择了阶数适当的平稳时间序列模型进行拟合和优化处理.
再次,使用实值核函数,构造出鞅变换拟积分函数,并利用MATLAB,对构造的函数进行了渐近逼近分析,,通过对不同鞅变换拟积分函数的渐近逼近分析,得出这些参数的拟最大似然估计.
最后,通过SAS软件,对三种不同的模型进行了预测,从而验证了该方法用于AR模型参数估计的有效性.
关键词核函数;积分变换;鞅变换估计函数;投影;最优鞅变换合并
Abstract
To a certain extent, consumer confidence index is a reflection of the status of economic development. This paper researches the parameters of the model estimation problem based on this index established by stationary time series model. Thesis as follows:
Firstly, paper introduces a new estimate of the parameters of stationary time series model estimation method and gives the proof of two. On the one hand, integral function is a function to be integral to the martingale transformate the orthogonal projection of space. On the other hand, when the kernel function selected from a countable concentration, the transform function can approximate integral function integral. These prooves to optimize the martingale transform estimation function provides a theoretical basis. Then paper proposes a conjecture for the martingale transform estimate function optimization problems.
Secondly, paper analyzes the consumer confidence index of the timing diagram. Through the stationary time series model identification methods, paper choices AR model. Then through SAS software, paper calculates the data autocorrelation and partil correlation coefficient and selectes the order of the appropriate stationary time series model fitting and optimization.
Thirdly, by using the real-valued kernel function, paper constructs a martingale transform to be integral function and by using MATLAB, paper analyzes the asymptotic approximation on the sructured function. It obtains the quasi-max