时间序列的新息预报

根据实际问题，针对有限个数据ｗｋ，ｗｋ－１，…，ｗ１，给出了Ｗｋ＋ｌ的严格的线性最小方差预报和实现这种预报的适时递推公式和计算方法，并与平稳预报进行比较，得到两者有渐近相等的一步预报误差方差。     

Dynamic factor models

Summary Factor models can cope with many variables without running into scarce degrees of freedom problems often faced in a regression-based analysis. In this article we review recent work on dynamic factor models that have become popular in macroeconomic policy analysis and forecasting. By means of an empirical application we demonstrate that these models turn out to be usefu in investigating macroeconomic problems.     

财经类高校课堂教学评价模型及应用

课堂教学及其评价是当前教学质量评估中的重要一环。文章根据财经高校教学特点,利用灰色系统多层次评价理论建立不同专家对不同教师课堂教学技能的评价模型,在案例应用中取得了较好的效果。     

饱和增长趋势预测的自适应方法

讨论了商业、市场中大量存在的饱和增长过程的自适应预测问题,详细分析了自适应增长趋势预测尤其是Kalman滤波方法涉及的模型、模型变换、递推初值确定及趋势外椎等技术问题。     

Bayesian break-point forecasting in parallel time series,with application to university admissions

A regular supply of applicants to Queen's University in Kingston, Ontario is provided by 65 high schools. Each high school can be characterized by a series of grading standards which change from year to year. To aid admissions decisions, it is desirable to forecast the current year's grading standards for all 65 high schools using grading standards estimated from past year's data. We develop and apply a Bayesian break-point time-series model that generates forecasts which involve smoothing across time for each school and smoothing across schools. “Break point” refers to a point in time which divides the past into the “old past” and the “recent past” where the yearly observations in the recent past are exchangeable with the observations in the year to be forecast. We show that this model works fairly well when applied to 11 years of Queen's University data. The model can be applied to other data sets with the parallel time-series structure and short history, and can be extended in several ways to more complicated structures.     

基于GERT随机网络的废弃回收预测模型研究

在阐述回收处理业务流程的基础上,分析其不确定性;运用随机网络系统模型的相关理论构建GERT网络模型,探讨产品回收再制造零部件和可再生材料的预测模型。该模型既可以预测出废弃产品返回数量、回收处理过程中的再造零部件和可再生材料的比例和数量,又可以预测出它们的期望返回时间。最后,以打印机的回收再制造为例,对模型进行了实际应用。     

中国2004年前11个月经济运行情况和2005年展望

文章对2004年前11个月经济运行的基本情况和本轮宏观调控的成效进行了阐述,并从定性和定量两个角度对2005年经济增长率和物价上涨率进行了分析和预测,最后对2005年宏观经济调控提出了一些政策性建议。     

The use of GARCH models in VaR estimation

We evaluate the performance of an extensive family of ARCH models in modeling the daily Value-at-Risk (VaR) of perfectly diversified portfolios in five stock indices, using a number of distributional assumptions and sample sizes. We find, first, that leptokurtic distributions are able to produce better one-step-ahead VaR forecasts; second, the choice of sample size is important for the accuracy of the forecast, whereas the specification of the conditional mean is indifferent. Finally, the ARCH structure producing the most accurate forecasts is different for every portfolio and specific to each equity index.     

基于自相关理论的GM(1,1)和GM(1,N)联合预测

通过引入自相关分析，将GM（1，1）与GM（1，N）两者的优点有机结合，运用GM（1，1）预测模型所需的数据量，达到GM（1，N）预测模型所具有的预测精度，减少灰色模型的预测误差。     

Convergence of Discount Time Series Dynamic Linear Models

This article studies the limiting behavior of multiple discount time series dynamic linear models (TSDLMs). It is shown that, under mild conditions, all discount TSDLMs converge to the constant (time-invariant) TSDLM. In particular, the limiting posterior precision matrix of the superposition of multiple discount TSDLMs is explored. For non seasonal models, the elements of the limiting posterior precision of the states are given in a recurrence relationship, while for seasonal models the solution of a linear system provides the elements of the respective limiting precision matrix. The proposed methodology uses canonical Jordan forms and it is illustrated with a detailed example of simulated data featuring both trend and seasonal time series.