A simulation study of the efficiency of empirical Bayes' estimators of multiple correlated probability vectors

Empirical Bayes' methods had been used by Brier, Zacks, and Marlow [1] for estimating performance characteristic vectors of success probabilities. The problem is that of estimating k-dimensional success probabilities of dependent binomial random variables, which are highly correlated. The present study reinforces the results of the previous one by showing, via simulations, that the relative efficiency of the empirical Bayes estimators, compared to the Stein-type and to the maximum-likelihood ones, is very high. This holds even if the success proportions are based on a small number of trials. We study the case of equicorrelation structure with positive correlations.     

A graphical aid for sensitivity analysis of estimated regression coefficients

A problem often arising in applied linear regression modeling is determining the appropriate weight to attach to each observation. In the extreme, the problem extends to the deletion of observations from a data base. Since the choice of weights, fitting criteria, and estimation procedure depend on the specific objectives of the modeling, universally applicable guidelines are virtually nonexistent. However, the sensitivity of analytic conclusions to weights assigned to “suspect” observations can be conveniently assessed using a graphical display. This report develops such a display based on a modeling of outliers which leads naturally to estimators based on a weighted least-squares criterion, and a data-analytic method for determining how much downweighting to impose on a specific subset of observations. This technique is illustrated with several examples, including one relating air pollution to human mortality.     

Waiting time distributions for transient bulk queues with general vehicle dispatching strategies

A numerical approach is presented for determining the waiting time distribution in a transient bulk-arrival, bulk-service queue. Vehicle departures from the queue are governed by a general dispatch strategy that includes holding with a variable release function and vehicle cancellations. The waiting time distribution of a customer (in a group) arriving at a given point in time is calculated by simulating the process in discrete time and determining at each step the probability the customer has left the system. The dispatch strategies require knowing the total length of the queue as well as the position a customer holds in the queue. An exact approach is compared to an accurate approximation which is 50 to 100 times faster. Comparisons are made with other approaches in the context of steady-state systems.     

An error components model of cost overruns and schedule slip on army R&D programs

What has been causing cost overruns and schedule slippages in Army major weapon-system R&D programs during the past ten years? This article addresses this question with emphasis on the effectiveness of an Army acquisition strategy entitled Total Risk Assessing Cost Estimating (TRACE). An empirical study employed a questionnaire and interviews with key personnel from all of the major Army Program Management Offices involved with R&D. The major research question was the following: What explanatory variables have been affecting R&D cost overruns and development time? This includes an evaluation of TRACE as a potential explanatory variable. Data was collected and analyzed using an error components multiple regression model. The major explanatory variables that appeared to explain cost overruns were technological risk of the program, education and experience of key program management office personnel, and the degree of “buy in” by the prime contractor. Strong statistical results indicate that TRACE is having little or no effect on cost overruns. In the case of development time, the major explanatory variables were seen to be technological risk of the program, testing, TRACE, education, and length of the R&D contract.     

Computer software development: Quality attributes,measurements, and metrics

Software metrics try to identify, define, and assign various indices of merit that can support the quantitative comparisons and evaluations of software in all phases of its life cycle. This article is a state-of-the-art and state-of-the-practice review of literature related to software quality measurements and metrics.     

Multiperiod allocation of limited resources: A minimax approach

We consider a multiperiod model in which limited resources are allocated among competing activities in each period. The objective is to minimize the maximum weighted deviation of the cumulative activity levels from the cumulative demands among all activities at all periods. All resources are assumed to be storable; that is, surpluses at one period can be used later on. This model is useful, for example, in multiperiod production planning for high-technology industries that assemble a large variety of circuit boards using numerous electronic components. The model is formulated with a minimax objective. We develop an efficient algorithm that can solve large-scale problems very quickly. At each iteration, the algorithm makes use of the solution to a relaxed problem to identify activities that should be permanently set to zero, as well as groups of activities that should have the same value.     

Two heuristics for the economic lot scheduling problem: An experimental study

In this article we present and test two heuristics for the economic lot scheduling problem. The first heuristic was developed by one of us (P.C. Geng) during Ph.D. research, while the other is a convergent implementation of an algorithm due to Doll and Whybark. We study the performance of these heuristics on a large set of test problems constructed using a new form of problem generation that yields random problems within an experimental design.