Bounding convergence rates for Markov chains: An example of the use of computer algebra

Kolassa and Tanner (J. Am. Stat. Assoc. (1994) 89, 697–702) present the Gibbs-Skovgaard algorithm for approximate conditional inference. Kolassa (Ann Statist. (1999), 27, 129–142) gives conditions under which their Markov chain is known to converge. This paper calculates explicity bounds on convergence rates in terms calculable directly from chain transition operators. These results are useful in cases like those considered by Kolassa (1999).     

A BAYESIAN INTERPRETATION OF MULTIPLE POINT ESTIMATES

Consider a large number of econometric investigations using different estimation techniques and/or different subsets of all available data to estimate a fixed set of parameters. The resulting empirical distribution of point estimates can be shown - under suitable conditions - to coincide with a Bayesian posterior measure on the parameter space induced by a minimum information procedure. This Bayesian interpretation makes it easier to combine the results of various empirical exercises for statistical decision making. The collection of estimators may be generated by one investigator to ensure the satisfaction of our conditions, or they may be collected from published works, where behavioral assumptions need to be made regarding the dependence structure of econometric studies.     

人力资源质量成长链及其多级混成研究

基于社会系统工程思想,本文首先提出了人力资源质量成长环和成长链的概念,然后分析了人力资源质量的多级混成过程。     

Complexity and Competition

Extensive‐form market games typically have a large number of noncompetitive equilibria. In this paper, we argue that the complexity of noncompetitive behavior provides a justification for competitive equilibrium in the sense that if rational agents have an aversion to complexity (at the margin), then maximizing behavior will result in simple behavioral rules and hence in a competitive outcome. For this purpose, we use a class of extensive‐form dynamic matching and bargaining games with a finite number of agents. In particular, we consider markets with heterogeneous buyers and sellers and deterministic, exogenous, sequential matching rules, although the results can be extended to other matching processes. If the complexity costs of implementing strategies enter players’ preferences lexicographically with the standard payoff, then every equilibrium strategy profile induces a competitive outcome.     

基于吉伯斯样本生成器的向量自回归模型选择

内容提要：向量自回归模型是多元时间序列分析中最常用的方法之一。在建立模型的过程中模型选择是非常重要的一个环节,如果候选模型不是很多时,可以通过比较每个模型的准则值如AIC、AICc、BIC或HQ进行模型选择。可是,当存在大量候选模型时,我们无法一一比较每个模型的准则值。为了解决这个问题,本文提出一个基于吉伯斯样本生成器的向量自回归模型选择方法,结果表明应用该方法能够从大量候选模型中准确、高效地确认准则值最小的模型。     

Chain graph models: topological sorting of meta-arrows and efficient construction of $${\mathcal{B}}$$ -essential graphs

Essential graphs and largest chain graphs are well-established graphical representations of equivalence classes of directed acyclic graphs and chain graphs respectively, especially useful in the context of model selection. Recently, the notion of a labelled block ordering of vertices was introduced as a flexible tool for specifying subfamilies of chain graphs. In particular, both the family of directed acyclic graphs and the family of “unconstrained” chain graphs can be specified in this way, for the appropriate choice of . The family of chain graphs identified by a labelled block ordering of vertices is partitioned into equivalence classes each represented by means of a -essential graph. In this paper, we introduce a topological ordering of meta-arrows and use this concept to devise an efficient procedure for the construction of -essential graphs. In this way we also provide an efficient procedure for the construction of both largest chain graphs and essential graphs. The key feature of the proposed procedure is that every meta-arrow needs to be processed only once.     

Estimating the grid of time-points for the piecewise exponential model

One of the greatest challenges related to the use of piecewise exponential models (PEMs) is to find an adequate grid of time-points needed in its construction. In general, the number of intervals in such a grid and the position of their endpoints are ad-hoc choices. We extend previous works by introducing a full Bayesian approach for the piecewise exponential model in which the grid of time-points (and, consequently, the endpoints and the number of intervals) is random. We estimate the failure rates using the proposed procedure and compare the results with the non-parametric piecewise exponential estimates. Estimates for the survival function using the most probable partition are compared with the Kaplan-Meier estimators (KMEs). A sensitivity analysis for the proposed model is provided considering different prior specifications for the failure rates and for the grid. We also evaluate the effect of different percentage of censoring observations in the estimates. An application to a real data set is also provided. We notice that the posteriors are strongly influenced by prior specifications, mainly for the failure rates parameters. Thus, the priors must be fairly built, say, really disclosing the expert prior opinion.     

基于JIT配送的3PL运输协调调度问题建模与分析

近年来,随着第三方物流(Third Party Logistics,3PL)的日益成熟,其服务的专业性越来越高。相当数量的制造商们把产品的运输与配送外包给3PL以缩短订单处理的时间。本文研究Just-in-Time(JIT)背景下由3PL主导的供应链中3PL协调调度问题。3PL给出运输工具的出发、到达时间、可用的运载容量及相应的价格。制造商根据其生产调度和订单配送要求,有选择的使用3PL的运输资源,以最小的成本达JIT配送的目的。本文建立了该问题的数学模型,并证明了相应的计算复杂度。最后通过仿真实验验证计算复杂度。     

基于二层规划的供应链契约谈判模型与求解

基于二层规划理论建立了一种形式化的契约谈判模型,并提供了基于模糊数学理论的交互式求解算法。以批量订货和价格折扣为例,分别研究了Stackclberg对策、集中式合作和基于二层规划的谈判合作三种策略下的契约机制。通过与另外两种策略的比较,初步得到采用谈判合作策略协调效果好、可执行性高的结论。     

需求具有价格敏感性的供应链收益共享契约设计研究

本文研究了供应链收益共享契约的协调问题。在综合考虑最终销售价格为内生变量和剩余产品残值与生产成本相关的情况下,建立了供应链收益共享契约协调模型,并借助报童模型对零售商和供应商的决策行为进行分析,给出零售商最优决策行为和契约参数φ取值范围的计算公式。最后进行了数值实例分析,验证了供应链收益共享契约的有效性。