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pro vyhledávání: '"Mariadassou, Mahendra"'
Analyzing high-dimensional count data is a challenge and statistical model-based approaches provide an adequate and efficient framework that preserves explainability. The (multivariate) Poisson-Log-Normal (PLN) model is one such model: it assumes cou
Externí odkaz:
http://arxiv.org/abs/2405.14711
Publikováno v:
Comput Stat (2021)
Statistical testing is classically used as an exploratory tool to search for association between a phenotype and many possible explanatory variables. This approach often leads to multiple testing under dependence. We assume a hierarchical structure b
Externí odkaz:
http://arxiv.org/abs/2009.13335
Akademický článek
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Statistical analysis of network is an active research area and the literature counts a lot of papers concerned with network models and statistical analysis of networks. However, very few papers deal with missing data in network analysis and we reckon
Externí odkaz:
http://arxiv.org/abs/1903.12488
Autor:
Jollet, Maxence, Mariadassou, Mahendra, Rué, Olivier, Pessemesse, Laurence, Ollendorff, Vincent, Ramdani, Sofiane, Vernus, Barbara, Bonnieu, Anne, Bertrand-Gaday, Christelle, Goustard, Bénédicte, Koechlin-Ramonatxo, Christelle
Publikováno v:
In The American Journal of Pathology October 2023
In multivariate statistics, the question of finding direct interactions can be formulated as a problem of network inference - or network reconstruction - for which the Gaussian graphical model (GGM) provides a canonical framework. Unfortunately, the
Externí odkaz:
http://arxiv.org/abs/1806.03120
The Latent Block Model (LBM) is a model-based method to cluster simultaneously the $d$ columns and $n$ rows of a data matrix. Parameter estimation in LBM is a difficult and multifaceted problem. Although various estimation strategies have been propos
Externí odkaz:
http://arxiv.org/abs/1704.06629
Many application domains such as ecology or genomics have to deal with multivariate non Gaussian observations. A typical example is the joint observation of the respective abundances of a set of species in a series of sites, aiming to understand the
Externí odkaz:
http://arxiv.org/abs/1703.06633
Autor:
Benoit, Gaëtan, Peterlongo, Pierre, Mariadassou, Mahendra, Drezen, Erwan, Schbath, Sophie, Lavenier, Dominique, Lemaitre, Claire
Background. Large scale metagenomic projects aim to extract biodiversity knowledge between different environmental conditions. Current methods for comparing microbial communities face important limitations. Those based on taxonomical or functional as
Externí odkaz:
http://arxiv.org/abs/1604.02412
Autor:
Camargo, Franciele Pereira, Sakamoto, Isabel Kimiko, Delforno, Tiago Palladino, Mariadassou, Mahendra, Loux, Valentin, Midoux, Cédric, Duarte, Iolanda Cristina Silveira, Silva, Edson Luiz, Bize, Ariane, Varesche, Maria Bernadete Amâncio
Publikováno v:
In Journal of Environmental Management 1 August 2021 291