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M.I., G., F. C., & L. H. - R. (2012).  PORT-PPWM extreme value index estimation. Proceedings of COMPSTAT 2012. 259-270., Jan Abstract2012_compstat2012.pdf

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M.I., G., L. H. - R., & F. C. (2013).  Refined Estimation of a Light Tail: An Application to Environmental Data. (Torelli, Nicola; Pesarin, Fortunato; Bar-Hen, Avner (Eds.), Ed.).Advances in Theoretical and Applied Statistics. 143-153., Jan: Springer Berlin Heidelberg Abstract
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Mateus, A., & Caeiro F. (2022).  Confidence Intervals for the Shape Parameter of a Pareto Distribution. AIP Conference Proceedings. 2425, Abstract
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Mateus, A., & Caeiro F. (2022).  Improved Shape Parameter Estimation for the Three-Parameter Log-Logistic Distribution. (Qichun Zhang, Ed.).Computational and Mathematical Methods. 2022, 1–13., feb: Hindawi Limited AbstractWebsite
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Mateus, A. M. X. F., & Caeiro F. A. G. G. (2015).  The difference-sign randomness test. NTERNATIONAL CONFERENCE OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING 2015. 1702, , 2015: American Institute of Physics Inc. Abstract

In this paper we review the properties of the difference-sign randomness test. First we analyse the exact andasymptotic distribution of the test statistic and provide a table with values for the exact distribution function, for samples ofsize n ≤ 32. Then, we also present several moments of the statistic test, under the null hypothesis of randomness and underthe hypothesis of the existence of a linear trend. Finally, we present an illustration of the test difference-sign to a real data set.In this paper we review the properties of the difference-sign randomness test. First we analyse the exact andasymptotic distribution of the test statistic and provide a table with values for the exact distribution function, for samples ofsize n ≤ 32. Then, we also present several moments of the statistic test, under the null hypothesis of randomness and underthe hypothesis of the existence of a linear trend. Finally, we present an illustration of the test difference-sign to a real data set.

Mateus, A., & Caeiro F. (2020).  A new class of estimators for the shape parameter of a Pareto model. Computational and Mathematical Methods. , nov: Wiley AbstractWebsite
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Mateus, A., Caeiro F., Gomes D. P., & Sequeira I. J. (2016).  Statistical analysis of extreme river flows. International Conference of Computational Methods in Sciences and Engineering 2016, ICCMSE 2016. 1790, , 2016/12/6: American Institute of Physics Inc. Abstract

Floods are recurrent events that can have a catastrophic impact. In this work we are interested in the analysis of a data set of gauged daily flows from the Whiteadder Water river, Scotland. Using statistic techniques based on extreme value theory, we estimate several extreme value parameters, including extreme quantiles and return periods of high levels.Floods are recurrent events that can have a catastrophic impact. In this work we are interested in the analysis of a data set of gauged daily flows from the Whiteadder Water river, Scotland. Using statistic techniques based on extreme value theory, we estimate several extreme value parameters, including extreme quantiles and return periods of high levels.

Mateus, A., & Caeiro F. (2018).  Exact and Approximate Probabilities for the Null Distribution of Bartels Randomness Test. Contributions to Statistics. 227–240.: Springer International Publishing Abstract
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