On estimating population characteristics from record-breaking observations. i. parametric results

Consider an experiment in which only record-breaking values (e.g., values smaller than all previous ones) are observed. The data available may be represented as X₁,K₁,X₂,K₂, …, where X₁,X₂, … are successive minima and K₁,K₂, … are the numbers of trials needed to obtain new records. We treat the problem of estimating the mean of an underlying exponential distribution, and we consider both fixed sample size problems and inverse sampling schemes. Under inverse sampling, we demonstrate certain global optimality properties of an estimator based on the “total time on test” statistic. Under random sampling, it is shown than an analogous estimator is consistent, but can be improved for any fixed sample size.     

Hybrid heuristics for minimum cardinality set covering problems

Minimum cardinality set covering problems (MCSCP) tend to be more difficult to solve than weighted set covering problems because the cost or weight associated with each variable is the same. Since MCSCP is NP-complete, large problem instances are commonly solved using some form of a greedy heuristic. In this paper hybrid algorithms are developed and tested against two common forms of the greedy heuristic. Although all the algorithms tested have the same worst case bounds provided by Ho [7], empirical results for 60 large randomly generated problems indicate that one algorithm performed better than the others.     

A stochastic network formulation for complex sequential processes

A network model incorporating stochastic features is considered. The model represents a complex sequential process where an object or system moves through a succession of states (nodes) and operating modes (classes) in the course of carrying out its function (fulfilling its purpose). Transitions between states and operating modes occur in a possibly random manner and require (consume) some resource in randomly varying amounts. We discuss the routing behavior and resource requirements of a typical object as it moves through (and eventually out of) the network. We then shift our focus from a single object and its odyssey to the network as a whole, where time is the resource and many objects are entering the network according to a possibly nonhomogeneous Poisson pattern; in this vein, we discuss the evolution of the network over time. Finally, we consider some applications of the formulation, and results.     

The Argentine dilemma: The Southern cone vis-à-vis the “contradictory duality of world reality”

The world has been faced with a contradiction since the end of the Cold War. On the one hand, there are factors that have led to complex multi-interdepen-dency; on the other, there is a process of global disintegration caused by those very same factors. It is in this context that the Southern Cone of South America has revealed a remarkable inequality in its balance of military power. If Argentina is taken as the center of gravity of both the sub-regions in the area, the Mercado Comun del Sur (Mercosur) and the Austral Cone, it is difficult to find a solution to this imbalance because the regional structure is experiencing the same contradictions as the world itself. What is clear is that the solution depends much more on the policies adopted by Argentina than those of Chile or Brazil. To solve this dilemma, Argentina needs credibility - something that requires fundamental internal change and substantial external support.     

Two-characteristic markov-type manpower flow models

A two-dimensional state space Markov Model of a Manpower System with special structure is analyzed. Examples are given from the military services. The probabilistic properties are discussed in detail with emphasis on computation. The basic equations of manpower stocks and flows are analyzed.     

Estimation of ordered parameters from k stochastically increasing distributions

There are given k (? 2) univariate cumulative distribution functions (c.d.f.'s) G(x; θ_i) indexed by a real-valued parameter θ_i, i=1,…, k. Assume that G(x; θ_i) is stochastically increasing in θ_i. In this paper interval estimation on the i^th smallest of the θ's and related topics are studied. Applications are considered for location parameter, normal variance, binomial parameter, and Poisson parameter.     

Stochastic duels with bursts

In this analysis we extend the theory of stochastic duels to include the situation where one of the contestants fires a single infinitely long burst at a fixed rate of fire and secondly where he fires fixed-length, fixed-rate of fire bursts randomly spaced. In both cases the opponent fires single rounds randomly spaced. Special cases and parameter effects are considered.