函件业务量的多元回归预测方法

函件业务是邮政的核心和基础业务，函件业务的预测对制定邮政企业发展规划具有十分重要的意义。首先介绍了影响函件业务量的主要因素，然后给出了建立函件业务量多元回归模型的方法，并用近年来的有关数据建立了函件业务量实际模型，对近三年的函件业务量进行了预测。     

一类半参数回归模型二阶段估计的渐近理论

考虑回归模型yi＝xiβ＋g（ti）＋ei，1≤i≤n，g为R1上未知函数，β为p×1维待估参数向量．基于近邻权函数利用文献[1]中给出的方法建立了β和g的估计量βn，gn，并且证明了它们具有很好的大样本性质     

自补图度序列的结构

自补图是图论中对称性很强的一类图,因而它有不少醒目的特点。本文讨论了自补图度序列的结构特性;除了点数是p=1(mod4)的自补图的度序列的中项外,其余的项皆成对出现。当点数是p=0(mod4)时,其所有的项都成对出现。最后给出的自补图度序列前K对和的上界。     

Using evolutionary computation to solve problems in nonparametric regression

This paper studies evolutionary mechanism of parameter selection in the construction of weight function for Nearest Neighbour Estimate in nonparametric regression. Construct an algorithm which adaptively evolves fine weight and makes good prediction about unknown points. The numerical experiments indicate that this method is effective. It is a meaningful discussion about practicability of nonparametric regression and methodology of adaptive model-building. Supported by the National Natural Science Foundation and 863 High Technology Project of China Ding Lixin: born in 1967, Ph.D. graduate student     

大豆根潜蝇预测预报方法的研究

在多年研究的基础上，查阅国内文献，针对大豆根潜蝇的田间调查、发生期预测、发生量预测及防治指标等问题进行了系统的阐述．对我国大豆根潜蝇的预测预报及综合防治工作具有指导作用和实用性。     

Correspondence on the selection of error measures for comparisons among forecasting methods

Clements and Hendry (1993) proposed the Generalized Forecast Error Second Moment (GFESM) as an improvement to the Mean Square Error in comparing forecasting performance across data series. They based their conclusion on the fact that rankings based on GFESM remain unaltered if the series are linearly transformed. In this paper, we argue that this evaluation ignores other important criteria. Also, their conclusions were illustrated by a simulation study whose relationship to real data was not obvious. Thirdly, prior empirical studies show that the mean square error is an inappropriate measure to serve as a basis for comparison. This undermines the claims made for the GFESM.     

家具销售中预测模型的研究

用灰色非线性建模理论，建立了家具销售方面的两个预测模型，为家具企业的生产、销售，提供了一个科学而又容易操作的决策方法。     

Application of intervention analysis to a road fatality series in ontario

Effect of an intervention on a road fatality time series is studied using (i) the usual intervention analysis of Box and Tiao (1975), and (ii) CUSUM charts for the one-step-ahead forecast errors. It is shown that the seat belt and speed limit legislations of the Ontario Government had some impact in bringing down the road toll level.     

Forecast evaluation and improvement using theil's decomposition

Forecasters are concerned with the accuracy of a forecast and whether the forecast can be modified to yield an improved performance. Theil has proposed statistics to measure forecast performance and to identify components of forecast error. However, the most commonly used of Theil's statistics have been shown to have serious shortcomings. This paper discusses Theil's decomposition of forecast error into bias, regression and disturbance proportions. Examples using price expectations and new housing starts data are given to show how decomposition suggests a linear correction procedure that may improve forecast accuracy.     

Time-series forecasting of the German unemployment rate

The purpose of the paper is to investigate the accuracy of forecasts derived from univariate and multivariate time-series models. An iterative method to adjust for impact assessment in univariate ARIMA models is discussed and illustrated for the German unemployment rate. Finally, we also examine the pros and cons of the impact assessment model in comparison with VAR models.