Estimación de conjuntos y convexidad
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Uno de los propósitos fundamentales de la estimación de conjuntos consiste en reconstruir un conjunto, como el soporte de una distribución, a partir de una muestra aleatoria de puntos (o de diferentes funcionales asociadas a ella). Para que la estimación pueda realizarse será necesario imponer ciertas restricciones geométricas. Una de las más importantes es la convexidad. En el presente trabajo estudiaremos su relevancia basándonos en el artículo Brunel, V.-E. (2018). Methods for Estimation of Convex Sets. Statistical Science, 33(4), 615–632.
One of the fundamental purposes of the set estimation is to reconstruct a set, such as the support of a distribution, from a random sample of points (or different functionals associated with it). In order for the estimation to be performed, certain geometric constraints must be imposed. One of the most important is convexity. In this paper, we will study its relevance based on the paper Brunel, V.-E. (2018). Methods for Estimation of Convex Sets. Statistical Science, 33(4), 615–632.
One of the fundamental purposes of the set estimation is to reconstruct a set, such as the support of a distribution, from a random sample of points (or different functionals associated with it). In order for the estimation to be performed, certain geometric constraints must be imposed. One of the most important is convexity. In this paper, we will study its relevance based on the paper Brunel, V.-E. (2018). Methods for Estimation of Convex Sets. Statistical Science, 33(4), 615–632.
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