Seminários do CEAUL
Extreme Value Laws and Point Processes of Rare Events for Chaotic Dynamical Systems
Ana Cristina Moreira Freitas
FEP and CMUP, Universidade do Porto
Ana Cristina Moreira Freitas
FEP and CMUP, Universidade do Porto
Conferência internacional em honra de Maria Ivette Gomes (CEAUL, FCUL).
ICRA7, in honour of Professor M. Ivete Gomes, will bring together researchers and practitioners who work on Risk Analysis in Cancer Research, Medicine, Health Sciences, Economics, Management, Industry, and Biostatistics. The Conference is a forum for presenting new theoretical and computational models and methods in these and other related topics.
Gathering excellence where Cameron excels: Combinatorics, Groups, Model Theory, Number Theory, Semigroups, Statistics, and more...
Havard Rue
King Abdullah University of Science and Technology, Saudi Arabia
Maria de Lourdes Centeno
CEMAPRE, ISEG - Universidade Lisboa
Ana Ferreira
IST-CEMAT / CEAUL
Two fundamental methods in Extreme Value Theory are the Block Maxima (BM) and the Peaks-Over-threshold (POT) and, two widely used methods of estimation in extremes when applying BM or POT are the maximum likelihood (ML) and probability weighted moment (PWM). We prove asymptotic normality of the estimators under the BM approach and maximum domain of attraction conditions. This permits to compare their asymptotic performance under BM and POT approaches.
Rahim Mahmoudvand
Dep. Statistics, Bu-Ali Sina University, Hamedan, Iran
This three-day short course (6-8 March 2017) will be on Reinsurance, lectured by Hansjoerg Albrecher (University of Lausanne) and Jef Teugels (KULeuven).
Daniel Peña
Dep. Estadística - Universidad Carlos III de Madrid
This short course is aimed to statisticians and other researchers who are interested in learning about Geoadditive Regression with Software BayesX (www.bayesx.org). Geoadditive regression i.e. penalised spline smoothing and structured additive distributional regression models provide a simple yet flexible possibility to introduce nonlinear covariate effects in any type of regression models.