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The principle of smooth fit is probably the most used tool to find solutions to optimal stopping problems of one-dimensional diffusions. It is important, e.g., in financial mathematical applications to understand in which kind of models and problems smooth fit can fail. In this paper we connect-in case of one-dimensional diffusions-the validity of smooth fit and the differentiability of excessive functions. The basic tool to derive the results is the representation theory of excessive functions;...
La información cuadrática es una buena alternativa a la información de Shannon para todos aquellos problemas que, por su naturaleza, interesa tratarlos con una utilidad no local. El objetivo de este trabajo es dar, para estas situaciones, un método secuencial de construcción de diseños para discriminación entre modelos, basado en la maximización de la información cuadrática.Después de una introducción, donde se resumen los conceptos y resultados principales sobre información cuadrática, se plantea...
The paper studies a new class of robust regression estimators based on the two-step least weighted squares (2S-LWS) estimator which employs data-adaptive weights determined from the empirical distribution or quantile functions of regression residuals obtained from an initial robust fit. Just like many existing two-step robust methods, the proposed 2S-LWS estimator preserves robust properties of the initial robust estimate. However, contrary to the existing methods, the first-order asymptotic behavior...
En este trabajo consideramos el problema de la evaluación multiatributo en términos de una función de valor vectorial que conduce a un espacio de criterios en el que suponemos es posible obtener información parcial secuencial sobre las preferencias la cual se traduce en conos definidos sobre el espacio de criterios. También consideramos dentro del esquema señalado la situación en la cual el decisor parte de un subconjunto del conjunto total de decisiones, introduciendo el conjunto K-eficiente aproximado...
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