Luis Angel García-Escudero

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Two key questions in Clustering problems are how to determine the number of groups properly and measure the strength of group-assignments. These questions are specially involved when the presence of certain fraction of outlying data is also expected. Any answer to these two key questions should depend on the assumed probabilisticmodel, the allowed group(More)
The presence of clusters in a data set is sometimes due to the existence of certain relations among the measured variables which vary depending on some hidden factors. In these cases, observations could be grouped in a natural way around linear and nonlinear structures and, thus, the problem of doing robust clustering around linear affine subspaces has(More)
The maximum likelihood estimation in the finite mixture of distributions setting is an ill-posed problem that is treatable, in practice, through the EM algorithm. However, the existence of spurious solutions (singularities and non-interesting local maximizers) makes difficult to find sensible mixture fits for non-expert practitioners. In this work, a(More)
The first η(6)-complexes of iridium and ruthenium coordinated to helicenes have been obtained. Hexahelicene (1), 2,15-dimethylhexahelicene (2), and 2,15-dibromohexahelicene (3) react with [Cp*IrCl(2)](2) and AgBF(4) in CD(3)NO(2) to afford quantitatively the complexes [Cp*Ir(η(6)-1)][BF(4)](2) (4A), [Cp*Ir(η(6)-2)][BF(4)](2) (5A), and(More)
The Duane plot is a simple and widely used graphical technique in the analysis of repairable systems. The fitting of a straight line to points in that graph serves to determine the behavior of the system assuming a power law process. However, the classical least squares fitting suffer from lack of robustness and it is specially heavily affected by the more(More)
The high prevalence of spurious solutions and the disturbing effect of outlying observations in mixture modeling are well known problems that pose serious difficulties for non-expert practitioners of this kind of models in different applied areas. An approach which combines the use of Trimmed Maximum Likelihood ideas and the imposition of restrictions on(More)
A robust estimator for a wide family of mixtures of linear regression is presented. Robustness is based on the joint adoption of the cluster weighted model and of an estimator based on trimming and restrictions. The selected model provides the conditional distribution of the response for each group, as in mixtures of regression, and further supplies local(More)