Felipe Osorio

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The aim of this paper is to derive local influence curvatures under various perturbation schemes for elliptical linear models with longitudinal structure. The elliptical class provides a useful generalization of the normal model since it covers both lightand heavy-tailed distributions for the errors, such as Student-t, power exponential, contaminated(More)
Nonlinear mixed–effects models are very useful to analyze repeated measures data and are used in a variety of applications. Normal distributions for random effects and residual errors are usually assumed, but such assumptions make inferences vulnerable to the presence of outliers. In this work, we introduce an extension of a normal nonlinear mixed–effects(More)
The Grubbs’ measurement model is frequently used to comparing several measuring devices. It is common to assume that the random terms have a normal distribution. However, such assumption makes the inference vulnerable to outlying observations whereas scale mixtures of normal distributions have been an interesting alternative to produce robust estimates(More)
“Concession schools” is an educational program that was lunched in 1999 in the city of Bogotá, Colombia. It consisted on a contract between a group of private schools and the public educational system in which private agents provide education for low-income people. This paper test three main hypothesis concerning the impact of concessions over quality of(More)
M. Abdelazizm Mohamed P. Acevedo D. Albach E. Albertini R. Alia G. A. Allen L. Aona M. Appelhans B. Appezzato S. Arndt E. Austen J. Bachelier H. Ballard A. M. Banaei Moghaddam K. Bardy J. Batley A. Baumel M. Beilstein A. Bello V. Bittrich S. Blackmore F. Blattner M. Bog T. Brown S. Bruun-Lund W. Buck P. Bures M. T. Buril S. Buzato J. Byng L. Carlon R.(More)
Abstract Generalized linear mixed models form a general class of random effects models for discrete and continuous response in the exponential family. Spatial GLMM are an extension of such models that allows us to fit spatial-dependent data. A popular model in this class is the probit-normal model. In this study we develop a novel exact algorithm to(More)
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