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Gomes, M. I., & Caeiro F. (2014).  Eficiency of partially reduced-bias mean-of-order-p versus minimum-variance reduced-bias extreme value index estimation. COMPSTAT 2014: 21th International Conference on Computational Statistics. 289-298., Jan, Geneve Abstractgomes_caeiro_compstat2014_reprint.pdf

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Caeiro, F., & Mateus A. (2018).  Empirical Power Study of the Jackson Exponentiality Test. Demography and Health Issues. 225–235.: Springer International Publishing Abstract
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Caeiro, F., & Gomes M. I. (2006).  Estimação de quantis elevados em estatística de extremos. Actas do XIII Congresso Anual da Sociedade Portuguesa de Estatística - "Ciência Estatística". 217-228.2006spe217-228.pdf
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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Caeiro, F., & Mateus A. (2022).  Exponential versus Generalized Exponential Distribution: a Computational Study. AIP Conference Proceedings. 2425, Abstract
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Caeiro, F. A. G. G., Mateus A. M. X. F., & Ramos L. P. C. (2015).  Extreme value analysis of the sea levels in Venice. PROCEEDINGS OF THE INTERNATIONAL CONFERENCE OF NUMERICAL ANALYSIS AND APPLIED MATHEMATICS 2014. , 2015: American Institute of Physics Inc. Abstract

The number of floods in the city of Venice has increased substantially in the last decades and can be explained bythe sea level rise and land subsidence. Using Statistics of Extremes we shall model the extreme behaviour of the sea level inVenice and quantify risk through the estimation of important parameters such as return periods of high levels.The number of floods in the city of Venice has increased substantially in the last decades and can be explained bythe sea level rise and land subsidence. Using Statistics of Extremes we shall model the extreme behaviour of the sea level inVenice and quantify risk through the estimation of important parameters such as return periods of high levels.