R ＆ D STRATEGIC INVESTMENT IN AN ASYMMETRICAL CASE

This article analyzes R ＆ D investment decisions in an asymmetrical case. The investment decisions share three important characteristics. First, the investment is completely irreversible. Second, there are two kinds of uncertainties over the future returns from the investment and over technology in R ＆ D process, respectively. Third, there is strategic competition in the asymmetrical case. This article presents the optimal investment threshold values and the optimal investment rule of high-efficient firm （leader）, and shows that the investment threshold values are reduced by competition of two firms. Finally, the mixed investment strategies for two firms, the probability that each firm separately exercises the option to invest, and the probability that two firms simultaneously exercise the option are given in the paper.     

模糊物元精细评价方法在油水井酸化选井选层中的应用

油水井酸化是油气藏常用的增产增注措施之一．酸化措施足否有效取决于多方面的因素，而选井选层是其中一个重要环节．本文采用模糊物元分析疗法，用油水井代表事物，评价因素代表特征，建立了复合模糊物元矩阵，对油田整个区块需要酸化作业的井位和对应层位进行了综合决策，排列出需要进行酸化的井位和层位的先后顺序，为进一步施工奠定了理论基础．该方法排除了人为因素的影响，达到了科学决策的目的．文中选用某油田六口井的实际资料进行了计算，其结果与实际情况一致．     

Robustness of alternative non‐linearity tests for SETAR models

In recent years there has been a growing interest in exploiting potential forecast gains from the non‐linear structure of self‐exciting threshold autoregressive (SETAR) models. Statistical tests have been proposed in the literature to help analysts check for the presence of SETAR‐type non‐linearities in an observed time series. It is important to study the power and robustness properties of these tests since erroneous test results might lead to misspecified prediction problems. In this paper we investigate the robustness properties of several commonly used non‐linearity tests. Both the robustness with respect to outlying observations and the robustness with respect to model specification are considered. The power comparison of these testing procedures is carried out using Monte Carlo simulation. The results indicate that all of the existing tests are not robust to outliers and model misspecification. Finally, an empirical application applies the statistical tests to stock market returns of the four little dragons (Hong Kong, South Korea, Singapore and Taiwan) in East Asia. The non‐linearity tests fail to provide consistent conclusions most of the time. The results in this article stress the need for a more robust test for SETAR‐type non‐linearity in time series analysis and forecasting. Copyright © 2004 John Wiley & Sons, Ltd.     

关于Dirichlet级数的一个注记

本文对一类Ｄｉｒｉｃｈｌｅｔ级教给出了的关系，此处Ｘ（Ｘ）＝Ｘｐ（Ｘ）是实数集合Ｐ的特征函数．     

双层钙钛矿Sr2FeMoO6，Ba2FeMoO6的电磁性质研究

分析了双层钙钛矿结构的锰氧化合物Sr2FeMoO6,Ba2FeMoO6物相结构和电磁学性质,对巨磁阻效应进行了探讨,揭示了Sr2FeMoO6样品为半导体导电性,Ba2FeMoO6样品为金属导电性.     

Banach空间中的幂级数方程

本文考虑Banach空间中形如x=u+sum from k=1 to ∞(a_kx~k)的幂级数方程,建立了一个比较定理,并将其应用于一定的非线性积分方程.     

正项级数的广义Cauchy判别法

对正项级数的Cauchy,判别法作了推广,得出正项级数的广义Cauchy判别法.使原来的Cauchy判别法成为该判别之特例,从而扩大了它的使用范围.     

一类新的非线性混合拟变分包含的灵敏性分析

研究了一类新的非线性混合拟变分包含的灵敏性问题，通过使用预解算子及不动点技巧，证明了这类含参数的变分包含的解的存在唯一性及连续性，推广了近期有关文献的一些结果。     

CRP复合材料板复合型裂纹扩展方向预测理论研究

本文对碳纤维增强的复合材料板裂纹扩展方向预测理论进行了研究。介绍了最新发展起来的复合材料Z断裂理论 ,并通过试验证明了新理论的正确性     

基于RBF网络的混沌时间序列的建模与多步预测

提出将RBF神经网络应用于混沌时间序列的建模与预测中 ,设计了一个三层RBF网络结构 ,说明了RBF网络用于混沌时间序列建模和预测时的基本性质。仿真结果表明 ,RBF网络模型对混沌时间序列有比较强的拟合能力和比较高的一步及多步预测精度。采用RBF网络进行混沌时间序列的建模和预测能够取得比其它方法好得多的效果。