A family of models for uniform and serial dependence in repeated measurements studies

Data arising from a randomized double-masked clinical trial for multiple sclerosis have provided particularly variable longitudinal repeated measurements responses. Specific models for such data, other than those based on the multivariate normal distribution, would be a valuable addition to the applied statistician's toolbox. A useful family of multivariate distributions can be generated by substituting the integrated intensity of one distribution into a second (outer) distribution. The parameters in the second distribution are then used to create a dependence structure among observations on a unit. These may either be a form of serial dependence for longitudinal data or of uniform dependence within clusters. These are respectively analogous to the Kalman filter of state space models and to copulas, but they have the major advantage that they do not require any explicit integration. One useful outer distribution for constructing such multivariate distributions is the Pareto distribution. Certain special models based on it have previously been used in event history analysis, but those considered here have much wider application.     

The Packaging of Efficiency in the Development of the Intermodal Shipping Container

Abstract

This paper addresses different forms of spatio-temporal ordering in the stowage and handling of cargo on board cargo vessels, as well as docksides. Whilst the introduction of containerisation profoundly altered the urban geographies of many large port cities, as well as devastating the communities built around maritime labour, the core argument developed in this paper concerns the incremental development of spatio-temporal ordering strategies and practices. In particular, it situates the intermodal shipping container within a trajectory reaching back to earlier forms of unitisation such as crates and pallets. In doing so the paper outlines a genealogy of packaged efficiencies, arguing that the central thread linking maritime cargo handling practices in the twentieth century is the unitisation of shape. However, it concludes that the intermodal container achieved global hegemony through the packaged systemic efficiencies of standardisation.     

The Pareto rule and strategic voting

This paper uses a particular choice rule over sets of alternatives under the Pareto rule. Starting from the sincere situation every strategic misrevelation of preference is shown to be an improvement for all voters. The existence of an equilibrium under successive misrepresentations by sincere voters is demonstrated.     

Measuring Tail Thickness to Estimate the Stable Index α: A Critique

A generalized Pareto or simple Pareto tail-index estimate above 2 has frequently been cited as evidence against infinite-variance stable distributions. It is demonstrated that this inference is invalid; tail index estimates greater than 2 are to be expected for stable distributions with α as low as 1.65. The nonregular distribution of the likelihood ratio statistic for a null of normality and an alternative of symmetric stability is tabulated by Monte Carlo methods and appropriately adjusted for sampling error in repeated tests. Real stock returns yield a stable α of 1.845 and reject iid normality at the .996 level.     

作业时间依赖顺序的拆卸线平衡多目标优化

在废旧产品拆卸时无先后关系约束的任务之间可能存在拆卸干扰，使任务作业时间依赖于拆卸顺序，导致产品总作业时间不确定，从而影响拆卸线的平衡。为此，考虑拆卸过程中任务间的相互干扰，以最小化拆卸成本和环境危害为目标，构建作业时间依赖顺序的拆卸线平衡多目标优化模型，并提出一种Pareto人工蜂群算法进行求解，采用混合生成法保证种群质量与多样性，设计变邻域深度搜索策略以提高雇佣蜂局部开采效率，为降低侦察蜂探测的盲目性采用基于外部存档的单点变异算子进行搜索。最后通过算例与实例验证算法的有效性以及平衡任务在拆卸线上分配的重要性。     

Extreme value index estimator using maximum likelihood and moment estimation

ABSTRACT

When a distribution function is in the max domain of attraction of an extreme value distribution, its tail can be well approximated by a generalized Pareto distribution. Based on this fact we use a moment estimation idea to propose an adapted maximum likelihood estimator for the extreme value index, which can be understood as a combination of the maximum likelihood estimation and moment estimation. Under certain regularity conditions, we derive the asymptotic normality of the new estimator and investigate its finite sample behavior by comparing with several classical or competitive estimators. A simulation study shows that the new estimator is competitive with other estimators in view of average bias, average MSE, and coefficient of variance of the new device for the optimal selection of the threshold.     

Bootstrap confidence intervals for the pareto index

In the present paper we develop second-order theory using the subsample bootstrap in the context of Pareto index estimation. We show that the bootstrap is not second-order accurate, in the sense that it fails to correct the first term describing departure from the limit distribution. Worse than this, even when the subsample size is chosen optimally, the error between the subsample bootstrap approximation and the true distribution is often an order of magnitude larger than that oi tue asymptotic approximation. To overcome this deficiency, we show that an extrapolation method, based quite literally on a mixture of asymptotic and subsample bootstrap methods, can lead to second-order correct confidence intervals for the Pareto index.     

CONDITIONAL INFERENCE PROCEDURES FOR THE PARETO AND POWER FUNCTION DISTRIBUTIONS BASED ON TYPE-II RIGHT CENSORED SAMPLES

In this paper we consider conditional inference procedures for the Pareto and power function distributions. We develop procedures for obtaining confidence intervals for the location and scale parameters as well as upper and lower n probability tolerance intervals for a proportion g, given a Type-II right censored sample from the corresponding distribution. The intervals are exact, and are obtained by conditioning on the observed values of the ancillary statistics. Since, for each distribution, the procedures assume that a shape parameter x is known, a sensitivity analysis is also carried out to see how the procedures are affected by changes in x.     

Risk Finance for Catastrophe Losses with Pareto‐Calibrated Lévy‐Stable Severities

For catastrophe losses, the conventional risk finance paradigm of enterprise risk management identifies transfer, as opposed to pooling or avoidance, as the preferred solution. However, this analysis does not necessarily account for differences between light‐ and heavy‐tailed characteristics of loss portfolios. Of particular concern are the decreasing benefits of diversification (through pooling) as the tails of severity distributions become heavier. In the present article, we study a loss portfolio characterized by nonstochastic frequency and a class of Lévy‐stable severity distributions calibrated to match the parameters of the Pareto II distribution. We then propose a conservative risk finance paradigm that can be used to prepare the firm for worst‐case scenarios with regard to both (1) the firm's intrinsic sensitivity to risk and (2) the heaviness of the severity's tail.     

最优司法判决结果的博弈解读——兼及法律方法的可操作性

最优判决结果应为司法活动永恒的最高追求.从博弈论的视角解读,最优的司法判决结果应当是一个合法的、具有可接受性的而且实现了利益最大化的判决结果,亦即纳什均衡基础之上帕累托最优的实现.为达到这一目标,法官在视角选择时应站在"局内的局外人"的立场,而在实际操作时采取"无为的独裁者"的策略.通过这一问题的分析还表明,法律方法应具有可操作性,并且应将其作为法律方法研究进一步深入拓展的突破点与基本目标之一.