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Oliveira Martins, João Paulo

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Now showing 1 - 5 of 5
  • Searching for the corner seismic moment in worldwide data
    Publication . Felgueiras, Miguel; Santos, Rui; Oliveira Martins, João Paulo
    In this paper the existence of the corner frequency value for the seismic moment distribution is investigated, analysing worldwide data. Pareto based distributions, usually considered as the most suitable to this type of data, are fitted to the most recent data, available in a global earthquake catalog. Despite the undeniable finite nature of the seismic moment data, we conclude that no corner frequency can be established considering the available data set. © 2015 AIP Publishing LLC.
  • Known Mean, Unknown Maxima? Testing the Maximum Knowing Only the Mean
    Publication . Santos, Rui; Oliveira Martins, João Paulo; Felgueiras, Miguel
    In the quantitative group testing problem, the use of the group mean to identify if the group maximum is greater than a prefixed threshold (infected group) is analyzed, using n independent and identically distributed individuals. Under these conditions, it is shown that the information of the mean is sufficient to classify each group as infected or healthy with low probability of misclassification when the underline distribution is a unilateral heavy-tailed distribution.
  • Estimation Through Array-Based Group Tests
    Publication . Oliveira Martins, João Paulo; Felgueiras, Miguel; Santos, Rui
    Pooling individual samples for batch testing is a common procedure for reducing costs. The recent use of multidimensional array algorithms, due to the emergence of robotic pooling, is an innovative way of pooling. We show that the two-dimensional array-based group tests can provide accurate estimates for the prevalence rate even for situations in which the traditional estimators, applied to one-dimensional arrays, are not valid. Hence, a computational script was developed to determine which prevalence rate estimate minimizes the sum of the squared deviations between the number of observed and expected rows and columns whose pooled sample had a positive test result. © 2017, National Statistical Institute. All rights reserved.
  • Three-dimensional array-based group testing algorithms with one-stage
    Publication . Oliveira Martins, João Paulo; Felgueiras, Miguel; Santos, Rui
    The use of three-dimensional array-based testing algorithms is more efficient and accurate in some situations than other more commonly used algorithms to protocol pooled samples testing. We evaluate the advantages of using of this complex pooling schemes with only one stage in the problem of estimation of the prevalence rate of some disease. Using simulation work, we show that it does not seem to exist any advantage in using three or even higher-dimensional arrays for this type of problem.
  • Testing the Maximum by the Mean in Quantitative Group Tests
    Publication . Martins, João Paulo; Santos, Rui; Sousa, Ricardo
    Group testing, introduced by Dorfman in 1943, increases the efficiency of screening individuals for low prevalence diseases. A wider use of this kind of methodology is restricted by the loss of sensitivity inherent to the mixture of samples. Moreover, as this methodology attains greater cost reduction in the cases of lower prevalence (and, consequently, a higher optimal batch size), the phenomenon of rarefaction is crucial to understand that sensitivity reduction. Suppose, with no loss of generality, that an experimental individual test consists in determining if the amount of substance overpasses some prefixed threshold l. For a pooled sample of size n, the amount of substance of interest is represented by (Y1, … , Yn), with mean (Formula Presented) and maximum Mn. The goal is to know if any of the individual samples exceeds the threshold l, that is, Mn > l. It is shown that the dependence between (Formula Presented) and Mn has a crucial role in deciding the use of group testing since a higher dependence corresponds to more information about Mn given by the observed value of (Formula Presented).