916 research outputs found

    Two simple control policies for a multicomponent maintenance system

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    Control Systems;Maintenance;controle-systemen

    A note on exponential dispersion models which are invariant under length-biased sampling

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    Length-biased sampling situations may occur in clinical trials, reliability, queueing models, survival analysis and population studies where a proper sampling frame is absent.In such situations items are sampled at rate proportional to their length so that larger values of the quantity being measured are sampled with higher probabilities.More specifically, if f(x) is a p.d.f. presenting a parent population composed of nonnegative valued items then the sample is practically drawn from a distribution with p.d.f. g(x) = xf(x)/E(X) describing the lengthbiased population.In this case the distribution associated with g is termed a length-biased distribution.In this note we present a unified approach for characterizing exponential dispersion models which are invariant, up to translations, under various types of length-biased sampling.The approach is rather simple as it reduces such invariance problems into differential equations in terms of the derivatives of the associated variance functions.sampling;variance;models;distribution;statistics

    Siebert As Algonquianist

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    Karl V. (van Duyn) Teeter learned Japanese as a U.S. Army draftee during the Korean War. Upon his discharge from the military in 1954 he went to Berkeley, majoring in Oriental Languages. He entered Berkeley ’s linguistics program and did fieldwork with the last speaker of Wiyot, a language indigenous to northern California that has since been demonstrated to be genetically related to all the Algonquian languages. After coming to Harvard in 1959 he studied Maliseet-Passamaquoddy and, for several years, chaired Harvard’s linguistics department. He is now Professor of Linguistics, Emeritus at Harvard. What follows is his assessment of Frank Siebert as an Algonquianist

    Approximations for the delivery splitting model

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    Consumer Demand;Operational Research;Stocks

    Group Testing Models with Processing Times and Incomplete Identification

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    We consider the group testing problem for a finite population of possibly defective items with the objective of sampling a prespecified demanded number of nondefective items at minimum cost.Group testing means that items can be pooled and tested together; if the group comes out clean, all items in it are nondefective, while a "contaminated" group is scrapped.Every test takes a random amount of time and a given deadline has to be met.If the prescribed number of nondefective items is not reached, the demand has to be satisfied at a higher (penalty) cost.We derive explicit formulas for the distributions underlying the cost functionals of this model.It is shown in numerical examples that these results can be used to determine the optimal group size.testing;sampling
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