Browsing by Author "San Martin, E"

Now showing 1 - 3 of 3
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    Definition and probabilistic properties of skew-distributions
    (ELSEVIER, 2002) Arellano Valle, RB; del Pino, G; San Martin, E
    The univariate, and multivariate skew-normal distributions have a number of intriguing properties. It is shown here that these hold for a general class of distributions, defined in terms of independence conditions on signs and absolute values. For this class, two stochastic representations become equivalent, one using conditioning on the positivity of a random vector and the other employing a vector of absolute values. General methods for computing moments and for obtaining the density function of a general skew-distribution are given. The case of spherical and elliptical distributions is briefly discussed. (C) 2002 Published by Elsevier Science B.V.
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    IRT models for ability-based guessing
    (SAGE PUBLICATIONS INC, 2006) San Martin, E; del Pino, G; De Boeck, P
    An ability-based guessing model is formulated and applied to several data sets regarding educational tests ill language and in mathematics. The formulation of the model is such that the probability of a correct guess does not only depend on the item but also oil the ability of the individual, weighted with a general discrimination parameter. By so doing, the possibility that the individual uses his or her ability to some extent for differentiating among responses while guessing is also considered. Some important properties of the model are described and compared with analogous properties of related models. After simulation studies, the model is applied to different data sets of the Chilean Sistema de Medicion de la Calidad de la Educacion (SIMCE) tests of mathematics and language. The conclusion of this analysis seems relevant-namely, that the examinees use their ability to guess in the language test but not in the mathematics test.
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    The local spatial autocorrelation and the kernel method for identifying black zones - A comparative approach
    (PERGAMON-ELSEVIER SCIENCE LTD, 2003) Flahaut, B; Mouchart, M; San Martin, E; Thomas, I
    This article aims to determine the location and the length of road sections characterized by a concentration of accidents (black zones). Two methods are compared: one based on a local decomposition of a global autocorrelation index, the other on kernel estimation. After explanation, both methods are applied and compared in terms of operational results, respective advantages and shortcomings, as well as underlying conceptual elements. The operationality of both methods is illustrated by an application to one Belgian road. (C) 2003 Elsevier Science Ltd. All rights reserved.