Browsing by Author "Osorio, Felipe"

Now showing 1 - 3 of 3
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    Addressing non-normality in multivariate analysis using the t-distribution
    (2023) Osorio, Felipe; Galea Rojas, Manuel Jesús; Henríquez, Claudio; Arellano Valle, Reinaldo Boris
    The main aim of this paper is to propose a set of tools for assessing non-normality taking into consideration the class of multivariate t-distributions. Assuming second moment existence, we consider a reparameterized version of the usual t distribution, so that the scale matrix coincides with covariance matrix of the distribution. We use the local influence procedure and the Kullback–Leibler divergence measure to propose quantitative methods to evaluate deviations from the normality assumption. In addition, the possible non-normality due to the presence of both skewness and heavy tails is also explored. Our findings based on two real datasets are complemented by a simulation study to evaluate the performance of the proposed methodology on finite samples.
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    Assessment of local influence for the analysis of agreement
    (2019) Leal, Carla; Galea Rojas, Manuel Jesús; Osorio, Felipe
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    Comparing two spatial variables with the probability of agreement
    (2024) Acosta Salazar, Jonathan Daniel; Vallejos, Ronny; Ellison, Aaron M.; Osorio, Felipe; de Castro, Mário
    Computing the agree ment betwee n 2 con tinuous sequences is of grea t interest in statistics when comparing 2 instruments or one instrument with a gold standard. The probability of agree ment quantifies the similarity between 2 variables of interest, and it is useful for determining what constitutes a practically important difference. In this article, we introduce a generalization of the PA for the treatment of spatial vari ables. Our proposal makes the PA dependent on the spatial lag. We establish the conditions for which the PA decays as a function of the distance lag for isotropic stationary and nonstationary spatial processes . Estimtion is addr essed through a first-order appr oxima tion that guarantees the asymp totic normality of the sample version of the PA. The sensitivity of the PA with respect to the covariance parame ters is studied for finite sample size. The new method is described and illustrated with real data involving autumnal changes in the green chromatic coordinate ( G cc ) , an index of “greeness ”that captures the phenological stage of tree leaves, is associ ated with carbon flux from econsys tems, and is estimated from repeated images of forest canopies.