Asymptotics for non-parametric likelihood estimation with doubly censored multivariate failure times

This paper considers non-parametric estimation of a multivariate failure time distribution function when only doubly censored data are available, which occurs in many situations such as epidemiological studies. In these situations, each of multivariate failure times of interest is defined as the elapsed time between an initial event and a subsequent event and the observations on both events can suffer censoring. As a consequence, the estimation of multivariate distribution is much more complicated than that for multivariate right- or interval-censored failure time data both theoretically and practically. For the problem, although several procedures have been proposed, they are only ad-hoc approaches as the asymptotic properties of the resulting estimates are basically unknown. We investigate both the consistency and the convergence rate of a commonly used non-parametric estimate and show that as the dimension of multivariate failure time increases or the number of censoring intervals of multivariate failure time decreases, the convergence rate for non-parametric estimate decreases, and is slower than that with multivariate singly right-censored or interval-censored data.     

Reputation and efficiency: A non-parametric assessment of America’s top-rated MBA programs

Widely publicized reports of fresh MBAs getting multiple job offers with six-figure annual salaries leave a long-lasting general impression about the high quality of selected business schools. While such spectacular achievement in job placement rightly deserves recognition, one should not lose sight of the resources expended in order to accomplish this result. In this study, we employ a measure of Pareto-Koopmans global efficiency to evaluate the efficiency levels of the MBA programs in Business Week’s top-rated list. We compute input- and output-oriented radial and non-radial efficiency measures for comparison. Among three tier groups, the schools from a higher tier group on average are more efficient than those from lower tiers, although variations in efficiency levels do occur within the same tier, which exist over different measures of efficiency.     

系统协同发展程度的DEA评价研究

协同发展是区域经济得以顺利、快速发展的客观要求和前提条件;是可持续发展基础性、前提性因素和实现手段.系统协同发展不是即生的,它是通过对原有系统不断的诊断、调整、评价,周而复始逐步实现的.对系统协同发展程度的评价是系统实现协同发展的前提、指导和路径.借助于DEA的方法,从系统协同发展的内容上,给出“协同”和“发展”的评价方法;从系统的结构上,给出系统内和系统间的“协同”和“发展”评价方法.     

Network DEA: A slacks-based measure approach

Traditional DEA models deal with measurements of relative efficiency of DMUs regarding multiple-inputs vs. multiple-outputs. One of the drawbacks of these models is the neglect of intermediate products or linking activities. After pointing out needs for inclusion of them to DEA models, we propose a slacks-based network DEA model, called Network SBM, that can deal with intermediate products formally. Using this model we can evaluate divisional efficiencies along with the overall efficiency of decision making units (DMUs).     

A unified vector optimization problem: complete scalarizations and applications

The aim of this article is to introduce and analyse a general vector optimization problem in a unified framework. Using a well-known nonlinear scalarizing function defined by a solid set, we present complete scalarizations of the solution set to the vector problem without any convexity assumptions. As applications of our results we obtain new optimality conditions for several classical optimization problems by characterizing their solution set.     

A new method for complete ranking of DMUs

So far numerous models have been proposed for ranking the efficient decision-making units (DMUs) in data envelopment analysis (DEA). But, the most shortcoming of these models is their two-stage orientation. That is, firstly we have to find efficient DMUs and then rank them. Another flaw of some of these models, like AP-model (A procedure for ranking efficient units in data envelopment analysis, Management Science, 39 (10) (1993) 1261–1264), is existence of a non-Archimedean number in their objective function. Besides, when there is more than one weak efficient unit (or non-extreme efficient unit) these models could not rank DMUs. In this paper, we employ hyperplanes of the production possibility set (PPS) and propose a new method for complete ranking of DMUs in DEA. The proposed approach is a one stage method which ranks all DMUs (efficient and inefficient). In addition to ranking, the proposed method determines the type of efficiency for each DMU, simultaneously. Numerical examples are given to show applicability of the proposed method.     

参数与非参数前沿方法在生产率效率测度中的应用

参数和非参数前沿方法是测度生产率效率的两种重要方法,本文构建了一个将二者结合起来的研究框架。在此基础上,以我国30个省份的第一产业为例,对各省份的农业生产率效率进行了测度和比较。虽然两种方法各有优缺点,但结合使用不仅能提高各自的准确度,也能优化各决策单元的投入与产出比例,同时也是进一步经济计量分析的一个重要参照系。     

A double projection algorithm for multi-valued variational inequalities and a unified framework of the method

In this paper, we propose a double projection algorithm for a generalized variational inequality with a multi-valued mapping. Under standard conditions, our method is proved to be globally convergent to a solution of the variational inequality problem. Moreover, we present a unified framework of projection-type methods for multi-valued variational inequalities. Preliminary computational experience is also reported.     

A dynamic benchmarking system for assessing the recovery of inpatients: Evidence from the neurorehabilitation process

The shortage of medical resources (mainly beds) is a critical and increasingly prevalent problem affecting hospitals. Of the factors that contribute to these shortages, the ambiguity and insufficiency of the criteria used to identify whether an inpatient should be discharged are among the most detrimental. To address this issue, this study applies data envelopment analysis (DEA) on existing inpatient data from the Neurorehabilitation Center at Toronto’s Bridgepoint Hospital to create a dynamic benchmarking system to evaluate the health stage of an inpatient ready to be discharged. Unlike the more traditional parametric techniques, DEA provides non-subjective benchmarking that does not require any prior specification of the production function making it a more desirable choice for this application. The dynamic model categorizes the inpatient’s discharge status as rejected, under observation, or approved. This new approach not only allows managers to gain insight into the potential causes of medical resource shortages, but also allows clinicians to treat inpatients more effectively based on their discharge categories. For validation, the results of the dynamic model were compared with actual inpatient discharge assessments provided by the Bridgepoint Hospital.     

A comment on dynamic DEA

This brief comment provides a modification of the dynamic DEA model of Amirteimoori which appeared recently in this journal. The goal is to more directly allow the actions in the present period to have impacts on the future.     

降低风险措施有效性综合评价的一种非参数方法

针对风险评估中提出的以下3个问题：（1）当投入量不增时,能否继续降低风险层次,（2）在风险层次不升高的情况下,能否降低投入量,（3）对于某一方案投入指标和风险指标是否还有进一步改进的可能性,给出了一种用于评价降低风险措施有效性的非参数方法（RDEA）,并对文[1]中的有关模型进行了进一步分析,运用偏序集理论给出了DEA有效的一个充要条件.最后,探讨了该方法在船舶工程领域中的应用.     

求DEA有效最速方向的一般方法

提出经验生产可能集的支撑超平面表示形式,在献[3]的基础上,对生产可能集内任意非DEA有效的决策单元,给出在生产可能集内,求解其DEA有效最速方向,使其最速达到DEA有效的一般方向,同时指出献[4]、[7]中的两处错误。     

Final-offer arbitration in major league baseball: A nonparametric analysis

This study extends the non-parametric methodology for empirical efficiency analysis to allow for a double frontier based on perspective and applies the model to final-offer arbitration in major league baseball. Arbitration eligible players perceive their worth relative to other players who earn more with no better performance. Owners, on the other hand, perceive a player's value relative to other players performing as well with lower salaries. The two different perspectives give rise to different perceived frontiers. The purpose of this paper is to analyze arbitration using this approach.     

Allocating the fixed cost as a complement of other cost inputs: A DEA approach

In cost allocation problem, traditional DEA approaches allocate the fixed cost among a group of decision making units (DMUs), and treat the allocated cost as an extra input of each DMU. If costs except for the fixed cost are regarded as inputs in the cost allocation problem, then it is obvious that the fixed cost is a complement of other inputs rather than an extra independent input. Therefore it is necessary to combine the allocated cost with other cost measures in cost allocation problem. Based on this observation, this paper investigates the relationship between the allocated cost and the DEA efficiency score and develops a DEA-based approach to allocate the fixed cost among various DMUs. An example of allocating advertising expenditure between a car manufacturer and its dealers is presented to illustrate the method proposed in this paper.     

The semi-Markov beta-Stacy process: a Bayesian non-parametric prior for semi-Markov processes.

The literature on Bayesian methods for the analysis of discrete-time semi-Markov processes is sparse. In this paper, we introduce the semi-Markov beta-Stacy process, a stochastic process useful for the Bayesian non-parametric analysis of semi-Markov processes. The semi-Markov beta-Stacy process is conjugate with respect to data generated by a semi-Markov process, a property which makes it easy to obtain probabilistic forecasts. Its predictive distributions are characterized by a reinforced random walk on a system of urns.

     

A modified complete ranking of DMUs using restrictions in DEA models

Alirezaee and Afsharian [1] have proposed a new index, namely, Balance Index, to rank DMUs. In this paper, we will use their examples to illustrate that the proposed index is not stable. As a result, the corresponding rankings are also unstable. Then we analyze where an error occurs in the new method for complete ranking of decision making units and amend it by introducing the Maximal Balance Index. The numeral example reports the reasonability of our methods.     

Profiling effects in industrial data mining by non-parametric DOE methods: An application on screening checkweighing systems in packaging operations

There is a growing interest in applying robust techniques for profiling complex processes in industry. In this work, we present an approach for analyzing fractional-factorial data by building distribution-free models suitable for dealing with replicated trials in search of non-linear effects. The technique outlined in this article is synthesized by implementing four key elements: (1) the data collection efficiency of non-linear fractional factorial designs, (2) the data compression capabilities of rank-sums for repetitive sampling schemes, (3) the rank-ordering as a means to transform data, and (4) the non-parametric screening for prominent effects where the normality and sparsity assumptions are waived. The technique is tested on four controlling factors for profiling the packaging weighing operations of a pharmaceutical enterprise. The robust data mining of repeated trials based on an L₉(3⁴) orthogonal array scheme with embedded uncontrolled noise is discussed extensively. The technique has been subjected to quality control as it is tested with well-defined artificial data. Concluding remarks involve contrasting this new technique with mainstream competing schemes.     

A simplified version of the DEA cost efficiency model

This short paper deals with a current cost efficiency model and decreases the number of its constraints as well as its variables, which leads to a strong reduction in the computational requirements.     

某些决策单元的EDA有效性的简便判别法

本给出了判别某些决策单元EDA有效性（C^2R或C^2GS^2）的简便方法。