479 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Centre National de la Recherche ScientifiqueFR192 papers
- Université Paris-SaclayFR78 papers
- Université de MontpellierFR75 papers
- AgroParisTechFR59 papers
- Centre de Coopération Internationale en Recherche Agronomique pour le DéveloppementFR56 papers
- Mathématiques, Informatique et Statistique pour l'Environnement et l'AgronomieFR44 papers
- Institut de Recherche pour le DéveloppementFR41 papers
- Institut National de la Recherche AgronomiqueMA39 papers
- Institut Agro MontpellierFR38 papers
- Institut national de recherche en sciences et technologies du numériqueFR38 papers
- Territoires, Environnement, Télédétection et Information SpatialeFR33 papers
- Université Grenoble AlpesFR32 papers
30 papers · 1 filter
A Top-Down Scale Approach for Multiscale Geographically and Temporally Weighted Regression
Ghislain Geniaux, César Martinez, Samuel Soubeyrand
This paper proposes tds mgtwr, a multiscale geographically and temporally weighted regression (MGTWR) model with covariate-specific spatial and temporal scales. The approach combin…
Gaussian copula correlation network analysis with application to multi-omics data
Ekaterina Tomilina, Florence Jaffrézic, Gildas Mazo
Reconstructing gene regulatory networks from large-scale heterogeneous data is a key challenge in biology. In multi-omics data analysis, networks based on pairwise statistical asso…
Simulating transgenerational hologenomes under selection with RITHMS
Solène Pety, Ingrid David, Andrea Rau +1
A holobiont is made up of a host organism together with its microbiota. In the context of animal breeding, the holobiont can be viewed as the single unit upon which selection opera…
One-Bit Total Variation Denoising over Networks with Applications to Partially Observed Epidemics
Claire Donnat, Olga Klopp, Nicolas Verzelen
This paper introduces a novel approach for epidemic nowcasting and forecasting over networks using total variation (TV) denoising, a method inspired by classical signal processing…
Modeling Extreme Events: Univariate and Multivariate Data-Driven Approaches
Gloria Buriticá, Manuel Hentschel, Olivier C. Pasche +2
This article summarizes the contribution of team genEVA to the EVA (2023) Conference Data Challenge. The challenge comprises four individual tasks, with two focused on univariate e…
A Bayesian Framework for Multivariate Differential Analysis
Marie Chion, Arthur Leroy
Differential analysis is a routine procedure in the statistical analysis toolbox across many applied fields, including quantitative proteomics, the main illustration of the present…
Automated calibration of consensus weighted distance-based clustering approaches using sharp
Barbara Bodinier, Dragana Vuckovic, Sabrina Rodrigues +3
In consensus clustering, a clustering algorithm is used in combination with a subsampling procedure to detect stable clusters. Previous studies on both simulated and real data sugg…
Ms.FPOP: An Exact and Fast Segmentation Algorithm With a Multiscale Penalty
Arnaud Liehrmann, Guillem Rigaill
Given a time series in with a piecewise constant mean and independent noises, we propose an exact dynamic programming algorithm to minimize a least square criterion with a mu…
Disentangling the structure of ecological bipartite networks from observation processes
Emre Anakok, Pierre Barbillon, Colin Fontaine +1
The structure of a bipartite interaction network can be described by providing a clustering for each of the two types of nodes. Such clusterings are outputted by fitting a Latent B…
A novel family of beta mixture models for the differential analysis of DNA methylation data: an application to prostate cancer
Koyel Majumdar, Romina Silva, Antoinette Sabrina Perry +5
Identifying differentially methylated cytosine-guanine dinucleotide (CpG) sites between benign and tumour samples can assist in understanding disease. However, differential analysi…
Variable selection in sparse multivariate GLARMA models: Application to germination control by environment
M. Gomtsyan, C. Lévy-Leduc, S. Ouadah +3
We propose a novel and efficient iterative two-stage variable selection approach for multivariate sparse GLARMA models, which can be used for modelling multivariate discrete-valued…
A Comprehensive Framework for the Evaluation of Individual Treatment Rules From Observational Data
François Grolleau, Francois Petit, Raphaël Porcher
Individualized treatment rules (ITRs) are deterministic decision rules that recommend treatments to individuals based on their characteristics. Though ubiquitous in medicine, ITRs…
Learning common structures in a collection of networks. An application to food webs
Saint-Clair Chabert-Liddell, Pierre Barbillon, Sophie Donnet
Let a collection of networks represent interactions within several (social or ecological) systems. We pursue two objectives: identifying similarities in the topological structures…
Performing global sensitivity analysis on simulations of a continuous-time Markov chain model motivated by epidemiology
Henri Mermoz Kouye, Gildas Mazo, Clémentine Prieur +1
In this paper we apply a methodology introduced in Navarro Jimenez et al (2016) in the framework of chemical reaction networks to perform a global sensitivity analysis on simulatio…
Automated calibration for stability selection in penalised regression and graphical models
Barbara Bodinier, Sarah Filippi, Therese Haugdahl Nost +2
Stability selection represents an attractive approach to identify sparse sets of features jointly associated with an outcome in high-dimensional contexts. We introduce an automated…
Querying multiple sets of -values through composed hypothesis testing
Tristan Mary-Huard, Sarmistha Das, Indranil Mukhopadhyay +1
Motivation: Combining the results of different experiments to exhibit complex patterns or to improve statistical power is a typical aim of data integration. The starting point of t…
High-dimensional modeling of spatial and spatio-temporal conditional extremes using INLA and Gaussian Markov random fields
Emma S. Simpson, Thomas Opitz, Jennifer L. Wadsworth
The conditional extremes framework allows for event-based stochastic modeling of dependent extremes, and has recently been extended to spatial and spatio-temporal settings. After s…
Modeling dependent survival data through random effects with spatial correlation at the subject level
Ajmal Oodally, Estelle Kuhn, Klara Goethals +1
Dynamical phenomena such as infectious diseases are often investigated by following up subjects longitudinally, thus generating time to event data. The spatial aspect of such data…
A variable selection approach for highly correlated predictors in high-dimensional genomic data
Wencan Zhu, Céline Lévy-Leduc, Nils Ternès
In genomic studies, identifying biomarkers associated with a variable of interest is a major concern in biomedical research. Regularized approaches are classically used to perform…
Detecting Abrupt Changes in the Presence of Local Fluctuations and Autocorrelated Noise
Gaetano Romano, Guillem Rigaill, Vincent Runge +1
Whilst there are a plethora of algorithms for detecting changes in mean in univariate time-series, almost all struggle in real applications where there is autocorrelated noise or w…
A Stochastic Block Model Approach for the Analysis of Multilevel Networks: an Application to the Sociology of Organizations
Saint-Clair Chabert-Liddell, Pierre Barbillon, Sophie Donnet +1
A multilevel network is defined as the junction of two interaction networks, one level representing the interactions between individuals and the other the interactions between orga…
Applicability and Interpretability of Hierarchical Agglomerative Clustering With or Without Contiguity Constraints
Nathanaël Randriamihamison, Nathalie Vialaneix, Pierre Neuvial
Hierarchical Agglomerative Classification (HAC) with Ward's linkage has been widely used since its introduction in Ward (1963). The present article reviews the different extensions…
A breakpoint detection in the mean model with heterogeneous variance on fixed time-intervals
Olivier Bock, Xavier Collilieux, François Guillamon +2
This work is motivated by an application for the homogeneization of GNSS-derived IWV (Integrated Water Vapour) series. Indeed, these GPS series are affected by abrupt changes due t…
Likelihood ratio test for variance components in nonlinear mixed effects models
Charlotte Baey, Paul-Henry Cournède, Estelle Kuhn
Mixed effects models are widely used to describe heterogeneity in a population. A crucial issue when adjusting such a model to data consists in identifying fixed and random effects…