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DTSTART;TZID=Europe/Brussels:20211202T130000
DTEND;TZID=Europe/Brussels:20211202T140000
DTSTAMP:20260430T163631
CREATED:20210817T073938Z
LAST-MODIFIED:20211129T215548Z
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SUMMARY:Camille Carpentier (Université de Namur)
DESCRIPTION:Title: Using degree distribution of ecological networks to predict their responses to random and targeted species removals \nFacing the current biodiversity crisis\, it is becoming increasingly important to be able to understand – and predict – the consequences of species removal on ecological networks. These complex networks can be described using simple metrics such as the number of species (nodes)\, the number of interactions between them (edges) and their degree distribution. Coupling these three pieces of information allows us to predict the topological impacts of species removal and provides a first tool to identify the most fragile networks and which species removals would be most deleterious. A fundamental step for this approach is to describe the relationship between the number of species and the number of interactions as a network-specific property\, whereas until now ecologists have assumed it as universal. The interaction-species relationship is based on the degree distribution of ecological networks (power-law\, exponential or uniform) could therefore be generalised to other types of complex networks and provide a first understanding of their resistance to node removal. \nThe seminar is in hybrid mode: \n_in person\, Room S08 (Faculty of Sciences) \n_online\, at this link
URL:https://www.naxys.be/event/camille-carpentier-universite-de-namur/
CATEGORIES:NAXYS Seminar
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DTSTART;TZID=Europe/Brussels:20211216T130000
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DTSTAMP:20260430T163631
CREATED:20210906T095150Z
LAST-MODIFIED:20211203T221526Z
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SUMMARY:Jeong Min Jeon (KU Leuven & Université de Namur)
DESCRIPTION:Title: Deconvolution estimation on hypersphere \nThis paper considers nonparametric estimation with contaminated data observed on the unit hypersphere $S^d$. For such data\, we consider deconvolution density estimation and regression analysis. Our methodology and theory are based on harmonic analysis on $S^d$ which is not well considered in statistics. We establish novel deconvolution density and regression estimators\, and study their asymptotic properties including the rates of convergence and asymptotic distributions. We also provide asymptotic confidence intervals. We present practical details on implementation as well as the results of simulation studies and real data analysis. \n\nThe seminar will be online at the following link
URL:https://www.naxys.be/event/jeong-min-jeon-ku-leuven-universite-de-namur/
CATEGORIES:NAXYS Seminar
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