基于在线算法的改进指数梯度投资组合策略

弱集成算法是对专家意见进行动态加权平均的在线学习算法。近年来,机器学习和人工智能等方法被用来研究在线投资组合问题。该文从弱集成算法的在线学习及其序列决策性角度出发,设计改进的指数梯度在线投资组合策略,以弥补指数梯度在线投资组合策略不能结合交易费用进行分析的缺陷。首先根据指数梯度在线投资组合策略的更新方法构建代表投资策略的专家意见池,并以此为基础应用弱集成算法加权集成专家意见得到改进的指数梯度在线投资组合策略,证明了该策略可与最优专家策略(基准策略)相媲美。其次将交易费用引入到改进的指数梯度在线投资组合策略中,进一步给出对应的投资策略,重要的是理论上证明了该策略实现的平均累积收益与最优专家策略实现的平均累积收益之间的差值存在渐进式下界,从而提高了指数梯度在线投资组合策略的实用性。最后利用国内外股票市场的历史数据进行实证分析,说明了改进的指数梯度在线投资组合策略的可行性和有效性。     

构建高效和谐“学生社区”的路径选择

从中国传统文化的角度来看,和谐可以凝聚人心,和谐可以团结力量,和谐可以推进发展,因此对于传承文化的教育机构,学校校园的高效和谐成为社会研究的一个永恒的主题。通过对构建高效和谐"学生社区"的意义进行阐述,概括出构建高效和谐"学生社区"的方法与途径,并对此方法与途径进行了论证和完善。     

医古文翻译：基于翻译适应选择论视角

随着中医的发展逐渐走向国际化,关于中医的中外交流日益增多,而对中医的翻译却又难以达到令人满意的水平。其难点主要在于保证医学信息的正确与完整的同时,又要将中医中文化内涵准确地传达。本文试图运用翻译适应选择论这一新译论,将医古文译者在翻译过程中的适应与选择通过语言维、文化维、交际维这三大维度进行分析和说明,以期为医古文翻译的障碍找出解决办法,提高翻译质量,促进文化交流。     

The multicriteria selection of products in technological diversification strategies: an application to the Spanish automotive industry based on AHP

The economic recession, the dynamism and complexity of the markets and the generalised globalisation of the world economy have forced many companies to rethink and reorganise their industrial strategies. Through identifying and taking advantage of the key technologies of a company, this work presents a new and original methodology for dealing with a general technological diversification process. The methodology, which includes an innovative cognitive perspective and its corresponding decisional tool (decision support system) has been used to select the best product in a process of technological diversification that, along with the key technologies, identifies the sub-levels consonant to the sub-technologies and applications to sectors and products. The multicriteria selection tool employed in the proposed methodology, based on the analytic hierarchy process, allows the integration of multiple scenarios, actors and criteria, both tangible and intangible. The methodology has been applied to a case study in the Spanish automotive auxiliary sector.     

Lag Length Selection for Unit Root Tests in the Presence of Nonstationary Volatility

A number of recent papers have focused on the problem of testing for a unit root in the case where the driving shocks may be unconditionally heteroskedastic. These papers have, however, taken the lag length in the unit root test regression to be a deterministic function of the sample size, rather than data-determined, the latter being standard empirical practice. We investigate the finite sample impact of unconditional heteroskedasticity on conventional data-dependent lag selection methods in augmented Dickey–Fuller type regressions and propose new lag selection criteria which allow for unconditional heteroskedasticity. Standard lag selection methods are shown to have a tendency to over-fit the lag order under heteroskedasticity, resulting in significant power losses in the (wild bootstrap implementation of the) augmented Dickey–Fuller tests under the alternative. The proposed new lag selection criteria are shown to avoid this problem yet deliver unit root tests with almost identical finite sample properties as the corresponding tests based on conventional lag selection when the shocks are homoskedastic.     

高校毕业生择业观对就业的影响分析

择业观是影响高校毕业生就业的一个重要因素，高校毕业生在就业过程中的“择业观”与他们最终的就业有着密切的联系。通过对2008届高校毕业生的择业心态问卷结果进行研究，并与他们最终的就业情况进行比较分析，总结出影响高校毕业生就业的几个最主要的择业观念，从而引导和帮助高校毕业生树立正确的择业观念。     

MODELING THE LIFETIME OF LONGITUDINAL ELEMENTS

In the study of the stochastic behaviour of the lifetime of an element as a function of its length, it is often observed that the failure time (or lifetime) decreases as the length increases. In probabilistic terms, such an idea can be expressed as follows. Let T be the lifetime of a specimen of length x, so the survival function, which denotes the probability that an element of length x survives till time t, will be given by S_T (t, x) = P(T > t/α(x), where α(x) is a monotonically decreasing function. In particular, it is often assumed that T has a Weibull distribution. In this paper, we propose a generalization of this Weibull model by assuming that the distribution of T is Generalized gamma (GG). Since the GG model contains the Weibull, Gamma and Lognormal models as special and limiting cases, a GG regression model is an appropriate tool for describing the size effect on the lifetime and for selecting among the embedded models. Maximum likelihood estimates are obtained for the GG regression model with α(x) = cx^b . As a special case this provide an alternative to the usual approach to estimation for the GG distribution which involves reparametrization. Related parametric inference issues are addressed and illustrated using two experimental data sets. Some discussion of censored data is also provided.     

Expert Systems

Summary

Expert systems are computer programs which embody the expertise of a human expert in order to consult and advise on a specific problem. It is now becoming feasible to apply expert systems technology to problems in the human services. This article describes what expert systems technology is and how it may be applied in human service practice. Finally, some of the promises and pitfalls of this new technology are addressed.     

A Critical Look at Some Analyses of Major League Baseball Salaries

At a data analysis exposition sponsored by the Section on Statistical Graphics of the ASA in 1988, 15 groups of statisticians analyzed the same data about salaries of major league baseball players. By examining what they did, what worked, and what failed, we can begin to learn about the relative strengths and weaknesses of different approaches to analyzing data. The data are rich in difficulties. They require reexpression, contain errors and outliers, and exhibit nonlinear relationships. They thus pose a realistic challenge to the variety of data analysis techniques used. The analysis groups chose a wide range of model-fitting methods, including regression, principal components, factor analysis, time series, and CART. We thus have an effective framework for comparing these approaches so that we can learn more about them. Our examination shows that approaches commonly identified with Exploratory Data Analysis are substantially more effective at revealing the underlying patterns in the data and at building parsimonious, understandable models that fit the data well. We also find that common data displays, when applied carefully, are often sufficient for even complex analyses such as this.     

An extension of bayesian measure of information to regression

This paper extends Lindley's measure of average information to the linear model, E(Y∣ß) = Xß. An expression which quantifies the average amount of information provided by the nxl vector of observations Y about the pxl vector of coefficient parameters ß will be derived. The effect of the structure of the regressor matrix, X, on the information measure is discussed. An information theoretic optimal design is characterized. Some applications are suggested.