Flow shop scheduling with deteriorating jobs under dominating machines

This paper addresses no-wait or no-idle flow shop scheduling problems with deteriorating jobs, i.e., jobs whose processing times are an increasing function of their starting time. A simple linear deterioration function is assumed and some dominating relationships between machines can be satisfied. It is shown that for the problems to minimize makespan or weighted sum of completion time, polynomial algorithms still exist, although these problems are more complicated than the classical ones. When the objective is to minimize maximum lateness or maximum tardiness, the solutions of a classical version may not hold.     

异质产品供应链定价控制权与零售商横向兼并效应分析

针对一部线性合约与供应商是否具有绝对定价控制权,比较分析零售商横向兼并集中度提高对消费者福利的影响.结果表明,(1)当供应商具有绝对定价控制权时,零售商横向兼并对消费者产生的影响取决于产品替代性程度大小:若替代性程度较高,则将产生有利影响,反之,将产生不利影响;(2)当供应商没有绝对定价控制权时,零售商横向兼并对消费者产生的影响取决于零售商兼并前的相对定价控制权强弱与兼并后的相对定价控制权增幅大小:若零售商在供应链中处于相对弱势地位,且零售商横向兼并使零售商的定价控制权增幅较大,则兼并将对消费者产生有利影响,否则,将对消费者产生不利影响.     

Pipage Rounding: A New Method of Constructing Algorithms with Proven Performance Guarantee

The paper presents a general method of designing constant-factor approximation algorithms for some discrete optimization problems with assignment-type constraints. The core of the method is a simple deterministic procedure of rounding of linear relaxations (referred to as pipage rounding). With the help of the method we design approximation algorithms with better performance guarantees for some well-known problems including MAXIMUM COVERAGE, MAX CUT with given sizes of parts and some of their generalizations.     

区域电力市场结构、所有权结构对发电企业效率影响的实证研究

以我国电力产业放松规制的实践为背景,基于产业组织理论构建了区域电力市场结构、所有权结构对发电企业效率影响的综合模型。以1999~2006年电力行业上市公司的统计数据为样本,采用分层线性模型回归方法对市场结构和所有权结构对发电企业效率的影响效果和影响路径进行了研究。实证结果表明:电力行业市场集中度下降有利于我国电力企业效率提升;电力行业国有所有权比重下降有利于企业效率的提升;电力行业企业数量和国有所有权比重对企业效率存在负向交互影响作用,但不显著。     

适应性市场假说及其在中国资本市场的实证

金融危机近些年爆发频繁,传统市场理论如有效市场假说和行为金融面对复杂的现实金融世界未能给出合理解释.Lo提出的适应性市场假说则弥合了这两个学派的分歧,逐渐引起了学术界的重视.本文尝试从动态市场效率、时变贝塔和技术交易策略演变这三个角度对适应性市场假说能否解释我国资本市场进行实证研究.研究发现:我国股票市场效率在动态变化,无效的时段与金融危机或政策巨变等重大事件联系密切;股市风格指数贝塔随市场环境变化而改变;技术交易策略绩效随投资者适应环境变化而演变.研究结果表明,适应性市场假说相比有效市场假说和经典资本资产定价模型,能够更好地解释我国资本市场上述现象.最后对投资者如何根据市场环境变化制定适应性投资策略给出几点建议.     

Practical Maximum Pseudolikelihood for Spatial Point Patterns(with Discussion)

This paper describes a technique for computing approximate maximum pseudolikelihood estimates of the parameters of a spatial point process. The method is an extension of Berman & Turner's (1992) device for maximizing the likelihoods of inhomogeneous spatial Poisson processes. For a very wide class of spatial point process models the likelihood is intractable, while the pseudolikelihood is known explicitly, except for the computation of an integral over the sampling region. Approximation of this integral by a finite sum in a special way yields an approximate pseudolikelihood which is formally equivalent to the (weighted) likelihood of a loglinear model with Poisson responses. This can be maximized using standard statistical software for generalized linear or additive models, provided the conditional intensity of the process takes an 'exponential family' form. Using this approach a wide variety of spatial point process models of Gibbs type can be fitted rapidly, incorporating spatial trends, interaction between points, dependence on spatial covariates, and mark information.     

Bayes linear analysis for graphical models: The geometric approach to local computation and interpretive graphics

This paper concerns the geometric treatment of graphical models using Bayes linear methods. We introduce Bayes linear separation as a second order generalised conditional independence relation, and Bayes linear graphical models are constructed using this property. A system of interpretive and diagnostic shadings are given, which summarise the analysis over the associated moral graph. Principles of local computation are outlined for the graphical models, and an algorithm for implementing such computation over the junction tree is described. The approach is illustrated with two examples. The first concerns sales forecasting using a multivariate dynamic linear model. The second concerns inference for the error variance matrices of the model for sales, and illustrates the generality of our geometric approach by treating the matrices directly as random objects. The examples are implemented using a freely available set of object-oriented programming tools for Bayes linear local computation and graphical diagnostic display.     

Orientation relationship in finite dimensional space

In the present article, we discuss the regression of a point on the surface of a unit sphere in d dimensions given a point on the surface of a unit sphere in p dimensions, where p may not be equal to d. Point projection is added to the rotation and linear transformation for regression link function. The identifiability of the model is proved. Then, parameter estimation in this set up is discussed. Simulation studies and data analyses are done to illustrate the model.     

Implementing Monte Carlo tests with p-value buckets

Software packages usually report the results of statistical tests using p-values. Users often interpret these values by comparing them with standard thresholds, for example, 0.1, 1, and 5%, which is sometimes reinforced by a star rating (***, **, and *, respectively). We consider an arbitrary statistical test whose p-value p is not available explicitly, but can be approximated by Monte Carlo samples, for example, by bootstrap or permutation tests. The standard implementation of such tests usually draws a fixed number of samples to approximate p. However, the probability that the exact and the approximated p-value lie on different sides of a threshold (the resampling risk) can be high, particularly for p-values close to a threshold. We present a method to overcome this. We consider a finite set of user-specified intervals that cover [0, 1] and that can be overlapping. We call these p-value buckets. We present algorithms that, with arbitrarily high probability, return a p-value bucket containing p. We prove that for both a bounded resampling risk and a finite runtime, overlapping buckets need to be employed, and that our methods both bound the resampling risk and guarantee a finite runtime for such overlapping buckets. To interpret decisions with overlapping buckets, we propose an extension of the star rating system. We demonstrate that our methods are suitable for use in standard software, including for low p-value thresholds occurring in multiple testing settings, and that they can be computationally more efficient than standard implementations.