An application of empirical bayes techniques to the simultaneous estimation of many probabilities

Consider the following situation: Each of N different combat units is presented with a number of requirements to satisfy, each requirement being classified into one of K mutually exclusive categories. For each unit and each category, an estimate of the probability of that unit satisfying any requirement in that category is desired. The problem can be generally stated as that of estimating N different K-dimensional vectors of probabilities based upon a corresponding set of K-dimensional vectors of sample proportions. An empirical Bayes model is formulated and applied to an example from the Marine Corps Combat Readiness Evaluation System (MCCRES). The EM algorithm provides a convenient method of estimating the prior parameters. The Bayes estimates are compared to the ordinary estimates, i.e., the sample proportions, by means of cross validation, and the Bayes estimates are shown to provide considerable improvement.     

Landmarks in defense literature

Izbrannye Proizvedennia. By M. V. Frunze. Moscow (1957)     

Analysis of project scheduling strategies in a client-contractor environment

In this article we consider a cost-minimization model to investigate scheduling strategies for multistaged projects in a client-contractor environment. This type of environment is symptomatic of temporal changes in project definition and scope. At prespecified epochs the client conducts an external evaluation of the project and either accepts or rejects the contractor's current work. The resulting uncertainty from the client's review is modeled via monotonically varying acceptance probabilities. The model is designed primarily to address the interaction between earliest-, intermediate-, and latest-start options and project-crashing stragies for a broad range of penalty costs. Theoretical results are introduced, while numerical examples for both exponentially and polynomially based acceptance probabilities are discussed.     

On the bivariate negative binomial distribution of mitchell and paulson

The bivariate negative binomial distribution of Mitchell and Paulson [17] for the case b = c = 0 is shown to be equivalent to the accident proneness model of Edwards and Gurland [4] and Subrahmaniam [19,20]. The diagonal series expansion of its joint probability function is then derived. Two other formulations of this distribution are also considered: (i) as a mixture model, which showed how it arises as the discrete analogue to the Wicksell-Kibble bivariate gamma distribution, and (ii) as a consequence of the linear birth-and-death process with immigration.     

State information lag markov decision process with control limit rule

In the framework of a discrete Markov decision process with state information lag, this article suggests a way for selecting an optimal policy using the control limit rule. The properties sufficient for an optimal decision rule to be contained in the class of control limit rules are also studied. The degradation in expected reward from that of the perfect information process provides a measure of the potential value of improving the information system.     

A reliability model with states of partial operation

This article generalizes the classical dichotomic reliability model to include states of partial operation. The generalized model can be considered as a special case of a general jump process. Both continuous and discrete state spaces are included. The relationship to cumulative damage shock models is discussed. Properties of the model are investigated and these are illustrated via examples. The equivalence of three forms of component independence is proved, but this equivalence does not generalize to the property of zero covariance. Alternative forms of series and parallel connections and the effect of component replacement are discussed.     

A hard knapsack problem

In this article we develop a class of general knapsack problems which are hard for branch and bound algorithms. The number of alternate optimal solutions for these problems grows exponentially with problem parameters. In addition the LP bound is shown to be ineffective. Computational tests indicate that these problems are truly difficult for even very small problems. Implications for the testing of algorithms using randomly generated problems is discussed.     

Warranty reserving

This paper considers a problem of warranty reserving, namely, the current practice of setting aside part of a product revenue to meet future claims arising from the warranty. We define a Compound Poisson stochastic model for warranty claims and reserve and obtain, using a sample paths technique, the long-run probability distribution of a warranty reserves, managed under alternative warranties and reserve policies.     

A duality model for a generalized minmax program

We consider a generalized minmax programming problem, and establish, under certain weaker convexity assumptions, the Fritz John sufficient optimality conditions for such a problem. A dual program is introduced and using those optimality conditions duality theorems are proved relating the dual and the primal. Duality for the generalized fractional programming problem is considered as an application of the results proved.