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Capítulo de Libro
Hadamard and Jensen inequalities for s-convex fuzzy processes
(Springer, 2004)
We give some inequalities of Hadamard and Jensen type for s-convex fuzzy processes. We also give some applications.
Capítulo de Libro
Continuity for s-convex fuzzy processes
(Springer, 2004)
In a previous paper we introduced the concept of s-convex fuzzy mapping and established some properties. In this work we study the continuity for s-convex fuzzy processes.
Artículo
A Monte Carlo comparison of three consistent bootstrap procedures
(Taylor & Francis, 2009-04)
Since bootstrap samples are simple random samples with replacement from the original sample, the information content of some bootstrap samples can be very low. To avoid this fact, some authors have proposed several variants ...
Artículo
Una generalización de la métrica de Hausdorff sobre C(Rn)
(Universidad Industrial de Santander, 2009)
En este trabajo hacemos una extensión de la métrica de Hausdorff H sobre C(Rn), el espacio de todos los conjuntos difusos cerrados en Rn, obteniendo una familia de métricas Df. Estudiamos algunas propiedades topológicas ...
Artículo
Influence Diagnostics in Regression with Complex Designs Through Conditional Bias
(Springer, 2005)
One of the a,rea~s of Statistics in ~ hich the influence a, nalysis has been ~ idely stu.died in the multiple linear regression model. Nevertheless, the influence diagnostics propo,sed in this context cannot be applied ...
Artículo
e-Encuestas Probabilísticas II. Los Métodos de Muestreo Probabilístico
(Instituto Nacional de Estadística, 2002)
En este trabajo se aborda fundamentalmente el estudio de las encuestas que utilizan la herramienta de Internet para su realización. En concreto su objetivo se centra en el planteamiento y desarrollo de diseños muestrales ...
Artículo
Reduced bootstrap for the median
(Academia Sinica (Institute of Statistical Science), 2004-10)
In this paper we study a modified bootstrap that consists of only considering those bootstrap samples satisfying k1 ≤ νn ≤ k2, for some 1 ≤ k1 ≤ k2 ≤ n, where νn is the number of distinct original observations in the ...