Publications

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2020
Gomes, M. I., Caeiro F., Figueiredo F., Henriques-Rodrigues L., & Pestana D. (2020).  Corrected-Hill versus partially reduced-bias value-at-risk estimation. Communications in Statistics: Simulation and Computation. 49, 867-885., Number 4 Abstract
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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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2014
2013
F., C., Gomes, & M.I. (2013).  Asymptotic Comparison at Optimal Levels of Minimum-Variance Reduced-Bias Tail-Index Estimators. Advances in Regression, Survival Analysis, Extreme Values, Markov Processes and Other Statistical Applications. 83-91., Jan: Springer Berlin Heidelberg Abstract
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F., C., & M.I. G. (2013).  A Class of Semi-parametric Probability Weighted Moment Estimators. Recent Developments in Modeling and Applications in Statistics. 139-147., Jan: Springer Berlin Heidelberg Abstract
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Ayana, F., & Frederico C. (2013).  Comparing several tests of randomness based on the difference of observations. 809-812., Jan, Number 1558 Abstract

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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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2012
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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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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2004
Gomes, M. I., Caeiro F., & Figueiredo F. (2004).  Bias reduction of a tail index estimator through an external estimation of the second-order parameter.. Statistics. 38, 497-510., Number 6 Abstract

{Summary: We first consider a class of consistent semi-parametric estimators of a positive tail index $\gamma$, parametrised in a tuning or control parameter $\alpha$. Such a control parameter enables us to have access for any available sample, to an estimator of the tail index $\gamma$ with a null dominant component of asymptotic bias and consequently with a reasonably flat mean squared error pattern, as a function of $k$, the number of top-order statistics considered.\par Such a control parameter depends on a second-order parameter $\rho$, which will be adequately estimated so that we may achieve a high efficiency relative to the classical Hill estimator [ıt B. M. Hill}, Ann. Stat. 3, 1163–1174 (1975; Zbl 0323.62033)] provided we use a number of top-order statistics larger than the one usually required for the estimation through the Hill estimator. An illustration of the behaviour of the estimators is provided, through the analysis of the daily log-returns on the Euro-US\$ exchange rates.}