Spatial Nonparametric Regression Estimation: Non-isotropic Case

Data collected on the surface of the earth often has spatial interaction. In this paper, a non-isotropic mixing spatial data process is introduced, and under such a spatial structure a nonparametric kernel method is suggested to estimate a spatial conditional regression. Under mild regularities, sufficient conditions are derived to ensure the weak consistency as well as the convergence rates for the kernel estimator. Of interest are the following: (1) All the conditions imposed on the mixing coefficient and the bandwidth are simple; (2) Differently from the time series setting, the bandwidth is found to be dependent on the dimension of the site in space as well; (3) For weak consistency, the mixing coefficient is allowed to be unsummable and the tendency of sample size to infinity may be in different manners along different direction in space; (4) However, to have an optimal convergence rate, faster decreasing rates of mixing coefficient and the tendency of sample size to infinity along each direction a     

三星时差定位系统的数据关联与定位算法

首先建立了三星时差定位算法的计算模型，得到了基于最大似然估计的定位迭代算法。然后分析了信号脉冲在不同卫星到达时间的关联问题，提出了一种建立在系统先验信息基础上的数据关联方法。最后，通过Monte-Carlo仿真实验，验证了数据关联方法和不同卫星面局下定位算法的性能。     

北京电话号码查询系统

本文介绍了新建的北京电话号码查询系统，内容包括系统配置、工作流程以及排队机、查询数据库、管理系统和系统连接功能等特点，并介绍了系统可拓展的业务。     

并行FORTRAN程序设计技术探索

简要叙述了并行程序设计语言ＣＭＦｏｒｔｒａｎ的计算模式、并行数据结构及其主要特征．并对Ｆｏｒｔｒａｎ７７和Ｆｏｒｔｒａｎ９０上的扩展部分作了概要描述．     

Assessing the predictive effectiveness of the variety seeking and reinforcement models

Prediction of customer choice behaviour has been a big challenge for marketing researchers. They have adopted various models to represent customers purchase patterns. Some researchers considered simple zero–order models. Others proposed higher–order models to represent explicitly customers tendency to seek [variety] or [reinforcement] as they make repetitive choices. Nevertheless, the question [Which model has the highest probability of representing some future data?] still prevails. The objective of this paper is to address this question. We assess the predictive effectiveness of the well–known customer choice models. In particular, we compare the predictive ability of the [dynamic attribute satiation] (DAS) model due to McAlister (Journal of Consumer Research, 91, pp. 141–150, 1982) with that of the well–known stochastic variety seeking and reinforcement behaviour models. We found that the stochastic [beta binomial] model has the best predictive effectiveness on both simulated and real purchase data. Using simulations, we also assessed the effectiveness of the stochastic models in representing various complex choice processes generated by the DAS. The beta binomial model mimicked the DAS processes the best. In this research we also propose, for the first time, a stochastic choice rule for the DAS model.     

EWSD(V9)中文话务统计管理软件

ＥＷＳＤ交换机已从Ｖ６．２版本升级为Ｖ９版本，两版本在话务数据和功能方面有很大改进与不同。文章介绍了Ｖ９版本在输出话务数据方面增加的新内容。     

无线电数据系统

欧广联(EBU)的无线电数据系统(RDS),是为在FM立体声广播中兼容传输附加信息而设计的。本文介绍了RDS的研究、发展与应用概况,阐述了RDS信号的产生、可传输的信息及其编码方法、数据格式和RDS接收机。     

软交换技术及其在下一代电信网中的应用

首先简要介绍了软交换的概念、协议和功能，在此基础上探讨了软交换在下一代电信网中的位置，并根据目前情况，提出了一种基于软交换的从现代电信网向下一代电信网过渡的方案。     

协变量区间删失时线性模型的参数估计

本文研究了当协变量为区间数据时的线性模型，通过构造区间数据变量的条件均值，得到了回归参数的估计，当协变量的分布已知时，证明了估计的无偏性与强相合性．时协变量的分布未知的情形也作了讨论．文中还作了若干模拟计算，从模拟的结果不难发现，利用本文提出的方法所获得的估计简便且具有较高的精度．     

Forecasting Winning Bid Prices on an Online Auction Market - Data Mining Approaches -

To solve information asymmetry problem on online auction, this study suggests and validates a forecasting model of winning bid prices. Especially, it explores the usability of data mining approaches, such as neural network and Bayesian network in building a forecasting model. This research empirically shows that, in forecasting winning bid prices on online auction, data mining techniques have showed better performance than traditional statistical analysis, such as logistic regression and multivariate regression.