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Selective editing as a stochastic optimization problem

Ignacio Arbués, Margarita González and Pedro Revilla
Instituto Nacional de Estadística
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  • Abstract
    In this paper, we approach the problem of selective editing by proposing a formal definition of selection strategy. Using this definition, the search for an efficient selective editing method can be expressed as an optimization problem with stochastic constraints. We show how to solve this problem by duality methods. We also present the results of a practical application.
  • Keywords: Selective Editing; Score Function; Stochastic Programming.
  • AMS Subject classifications: 90C15, 90C46, 90C90.
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