2 citations · 3 across the 6 of their papers we have counts for
6 papers
Inferring the presence and abundance of rare waterbirds species from scarce data
Barbara Bricout, Laura Dami, Pierre Defos du Rau +3
Abundance data are used in ecology for species monitoring and conservation. These count data often display several specific characteristics like numerous missing data, high varianc…
A Markov switching discrete-time Hawkes process: application to the monitoring of bats behavior
Anna Bonnet, Stéphane Robin
Over the past few decades, the Hawkes process has become a popular framework for modeling temporal events thanks to its flexibility to capture different dependency structures. The…
Online and Offline Robust Multivariate Linear Regression
Antoine Godichon-Baggioni, Stephane S. Robin, Laure Sansonnet
We consider the robust estimation of the parameters of multivariate Gaussian linear regression models. To this aim we consider robust version of the usual (Mahalanobis) least-squar…
Composite likelihood inference for the Poisson log-normal model
Julien Stoehr, Stephane S. Robin
The Poisson log-normal model is a latent variable model that provides a generic framework for the analysis of multivariate count data. Inferring its parameters can be a daunting ta…
Multiple change-point detection for Poisson point processes
C. Dion-Blanc, D. Hawat, E. Lebarbier +1
The aim of change-point detection is to identify behavioral shifts within time series data. This article focuses on scenarios where the data is derived from an inhomogeneous Poisso…
Modelling overdispersion heterogeneity in differential expression analysis using mixtures
Elisabetta Bonafede, Franck Picard, Stéphane Robin +1
Next-generation sequencing technologies now constitute a method of choice to measure gene expression. Data to analyze are read counts, commonly modeled using Negative Binomial dist…