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Caeiro, F. A. G. G., & Mateus A. M. X. F. (2014).  An R implementation of several randomness tests. AIP Conference Proceedings. 531 - 534., 2014/1/1 Abstract

In many statistic methods, including distribution-free methods, we assume to work with random samples. In this note, we present randtests: an R package implementation of several nonparametric randomness tests. After a brief description of the tests included in the package, we present an application to real data sets in the field of Agricultural.In many statistic methods, including distribution-free methods, we assume to work with random samples. In this note, we present randtests: an R package implementation of several nonparametric randomness tests. After a brief description of the tests included in the package, we present an application to real data sets in the field of Agricultural.

Caeiro, F., & Gomes M. I. (2006).  Redução de viés na estimação semi-paramétrica de um parâmetro de escala. Actas do XIII Congresso da SPE - "Ciência Estatística". 127-148.2006spe_127-148.pdf
Cabral, I., Caeiro F., & Gomes I. M. (2016).  Redução do viés do estimador de Hill: uma nova abordagem. Estatística: Progressos e Aplicações. 73 - 84., 2016/11 Abstract
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F., C., & M.I. G. (2012).  A Reduced Bias Estimator of a 'Scale' Second Order Parameter. 1114-1117., Jan, Number 1479 Abstract

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Cabral, I., Caeiro F., & Gomes I. M. (2016).  Reduced bias Hill estimators. International Conference of Computational Methods in Sciences and Engineering 2016, ICCMSE 2016. 1790, , 2016/12/6: American Institute of Physics Inc. Abstract

For heavy tails, classical extreme value index estimators, like the Hill estimator, are usually asymptotically biased. Consequently those estimators are quite sensitive to the number of top order statistics used in the estimation. The recent minimum-variance reduced-bias extreme value index estimators enable us to remove the dominant component of asymptotic bias and keep the asymptotic variance of the new estimators equal to the asymptotic variance of the Hill estimator. In this paper a new minimum-variance reduced-bias extreme value index estimator is introduced, and its non degenerate asymptotic behaviour is studied. A comparison with another important minimum-variance reduced-bias extreme value index estimator is also provided.For heavy tails, classical extreme value index estimators, like the Hill estimator, are usually asymptotically biased. Consequently those estimators are quite sensitive to the number of top order statistics used in the estimation. The recent minimum-variance reduced-bias extreme value index estimators enable us to remove the dominant component of asymptotic bias and keep the asymptotic variance of the new estimators equal to the asymptotic variance of the Hill estimator. In this paper a new minimum-variance reduced-bias extreme value index estimator is introduced, and its non degenerate asymptotic behaviour is studied. A comparison with another important minimum-variance reduced-bias extreme value index estimator is also provided.

Gomes, M. I., Caeiro F., Figueiredo F., Henriques-Rodrigues L., & Pestana D. (2020).  Reduced-bias and partially reduced-bias mean-of-order-p value-at-risk estimation: a Monte-Carlo comparison and an application. Journal of Statistical Computation and Simulation. 90, 1735-1752., Number 10 Abstract
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Caeiro, F., & Henriques-Rodrigues L. (2019).  Reduced-bias kernel estimators of a positive extreme value index. Mathematical Methods in the Applied Sciences. 42, 5867-5880., Number 17 Abstract
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Caeiro, F., Gomes M. I., & Rodrigues L. H. (2009).  Reduced-bias tail index estimators under a third-order framework.. Commun. Stat., Theory Methods. 38, 1019-1040., Number 7 Abstract

{Summary: We are interested in the comparison, under a third-order framework, of classes of second-order, reduced-bias tail index estimators, giving particular emphasis to minimum-variance reduced-bias estimators of the tail index $\gamma$. The full asymptotic distributional properties of the proposed classes are derived under a third-order framework and the estimators are compared with other alternatives, not only asymptotically, but also for finite samples through Monte Carlo techniques. An application to the log-exchange rates of the Euro against the USA Dollar is also provided.}

Caeiro, F. (2003).  Redução de viés em estimadores do índice de cauda. Actas do X Congresso Anual da SPE - “Literacia e Estatística”. 187-199., Porto, Portugalspe2002_187-199.pdf
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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Caeiro, F., & Gomes I. M. (2015).  Revisiting the maximum likelihood estimation of a positive extreme value index. Journal Of Statistical Theory And PracticeJournal Of Statistical Theory And Practice. 9(1), 200 - 218., 2015/1/13 AbstractWebsite

In this article, we revisit Feuerverger and Halls maximum likelihood estimation of the extreme value index. Based on those estimators we propose new estimators that have the smallest possible asymptotic variance, equal to the asymptotic variance of the Hill estimator. The full asymptotic distributional properties of the estimators are derived under a general third-order framework for heavy tails. Applications to a real data set and to simulated data are also presented.In this article, we revisit Feuerverger and Halls maximum likelihood estimation of the extreme value index. Based on those estimators we propose new estimators that have the smallest possible asymptotic variance, equal to the asymptotic variance of the Hill estimator. The full asymptotic distributional properties of the estimators are derived under a general third-order framework for heavy tails. Applications to a real data set and to simulated data are also presented.