Small-Sample Properties of GMM-Based Wald Tests

This article assesses the small-sample properties of generalized-method-of-moments-based Wald statistics by using (a) a vector white-noise process and (b) an equilibrium business-cycle model as the data-generating mechanisms. In many cases, the small-sample size of the Wald tests exceeds its asymptotic size and increases sharply with the number of hypotheses being jointly tested. We argue that this is mostly due to difficulty in estimating the spectral-density matrix of the residuals. Estimators of this matrix that impose restrictions implied by the model or the null hypothesis substantially improve the properties of the Wald statistics.     

A genetic algorithm for assembly line balancing

Assembly line balancing is a very important aspect in any mass production setup. However, finding the optimal balance is a very difficult proposition because of the computational complexity involved. Hence sub-optimal solutions are preferred over optimal solutions. In this work, a genetic algorithm (GA) is presented for obtaining good quality solutions for assembly line balancing problems. A major feature of GA is the ability to take care of a variety of objective functions. A modified GA working with two populations, one of which allows infeasible solutions, and exchange of specimens at regular intervals is proposed for handling irregular search spaces. The experimental results obtained with a single population, as well as two populations are encouraging.     

THE LOG-EIG DISTRIBUTION: A NEW PROBABILITY MODEL FOR LIFETIME DATA

ABSTRACT

In this paper, we propose a new probability model called the log-EIG distribution for lifetime data analysis. Some important properties of the proposed model and maximum likelihood estimation of its parameters are discussed. Its relationship with the exponential inverse Gaussian distribution is similar to that of the lognormal and the normal distributions. Through applications to well-known datasets, we show that the log-EIG distribution competes well, and in some instances even provides a better fit than the commonly used lifetime models such as the gamma, lognormal, Weibull and inverse Gaussian distributions. It can accommodate situations where an increasing failure rate model is required as well as those with a decreasing failure rate at larger times.     

论思想道德修养与法律基础课对大学生社会规则意识的培育

良好的社会规则习惯是现代公民的必备品质,然而,当代大学生社会规则意识令人堪忧,原因是多方面的。思想道德修养与法律基础课担负着大学生思想道德教育和法律教育的任务,为更好地培育大学生社会规则意识,教学需要转变理念、创新内容、拓展实践。     

Bayesian Dynamic Factor Models and Portfolio Allocation

We discuss the development of dynamic factor models for multivariate financial time series, and the incorporation of stochastic volatility components for latent factor processes. Bayesian inference and computation is developed and explored in a study of the dynamic factor structure of daily spot exchange rates for a selection of international currencies. The models are direct generalizations of univariate stochastic volatility models and represent specific varieties of models recently discussed in the growing multivariate stochastic volatility literature. We discuss model fitting based on retrospective data and sequential analysis for forward filtering and short-term forecasting. Analyses are compared with results from the much simpler method of dynamic variance-matrix discounting that, for over a decade, has been a standard approach in applied financial econometrics. We study these models in analysis, forecasting, and sequential portfolio allocation for a selected set of international exchange-rate-return time series. Our goals are to understand a range of modeling questions arising in using these factor models and to explore empirical performance in portfolio construction relative to discount approaches. We report on our experiences and conclude with comments about the practical utility of structured factor models and on future potential model extensions.     

Estimation and selection procedures in regression: An L1 approach

The authors consider the problem of estimating a regression function go involving several variables by the closest functional element of a prescribed class _G that is closest to it in the L₁ norm. They propose a new estimator ? based on independent observations and give explicit finite sample bounds for the L₁distance between ?g and go. They apply their estimation procedure to the problem of selecting the smoothing parameter in nonparametric regression.     

A simple approach for varying-coefficient model selection

In varying-coefficient models, an important question is to determine whether some of the varying coefficients are actually invariant coefficients. This article proposes a penalized likelihood method in the framework of the smoothing spline ANOVA models, with a penalty designed toward the goal of automatically distinguishing varying coefficients and those which are not varying. Unlike the stepwise procedure, the method simultaneously quantifies and estimates the coefficients. An efficient algorithm is given and ways of choosing the smoothing parameters are discussed. Simulation results and an analysis on the Boston housing data illustrate the usefulness of the method. The proposed approach is further extended to longitudinal data analysis.     

粤语-普通话讲话者言语产生中的词汇选择机制初探

以熟练非平衡粤语-普通话讲话为被试，考察粤一普讲话者言语产生中的词汇选择机制。结果发现，在预期切换条件下。切换至粤语（熟练方言）和切换至普通话（相对熟练方言）的切换代价相当；在无预期切换条件下，切换至普通话的切换代价较切换至粤语的切换代价大。熟练非平衡粤-普讲话者的词汇选择机制受语言熟练程度的差异以及任务类型的共同影响。     

论社会需求是翻译选择的决定因素

本文从翻译选择的三个方面——文本内容、翻译方法、意识形态之选择——论证了只有社会需求才是译者多维选择的依据。这与胡庚申教授的翻译生态学理论并不矛盾。翻译生态学认为,翻译就是以译者为中心的多维选择与适应。本文认为,只有社会需求才是译者多维选择的决定因素,只有依据社会需求作出的选择,才能适应和促进社会发展,译作才能被社会接受。     

清代惠陵工程选址始末

选址是中国古代皇家陵寝建筑工程最为关键的环节,文章通过选取清代晚期的惠陵工程为实例,旨在以点代面,揭示清代皇家陵寝选址的详细程序。采用实地调研和文献整理相结合的方法,在对传世＂样式雷＂图档和相关历史文献进行深入研究的基础上,详细介绍了惠陵工程从选派人员、实地踏勘、画图贴说、钦定吉壤等陵寝选址各个环节和具体操作程序。对中国古代陵寝风水理论的实质和选址程序等研究都具有重要的价值和意义。