4 citations · 8 across the 7 of their papers we have counts for
10 papers
Extending the saemix package for R to fit non Gaussian outcomes
Emmanuelle Comets, Maud Delattre, Belhal Karimi
Background and Objectives: Longitudinal data are increasingly collected in clinical trials to provide information on treatment action and disease evolution. The trajectory of conti…
Quasi-likelihood inference for SDE with mixed-effects observed at high frequency
Maud Delattre, Hiroki Masuda
We consider statistical inference for a class of dynamic mixed-effect models described by stochastic differential equations whose drift and diffusion coefficients simultaneously de…
Efficient preconditioned stochastic gradient descent for estimation in latent variable models
Charlotte Baey, Maud Delattre, Estelle Kuhn +2
Latent variable models are powerful tools for modeling complex phenomena involving in particular partially observed data, unobserved variables or underlying complex unknown structu…
Bayesian high-dimensional covariate selection in non-linear mixed-effects models using the SAEM algorithm
Marion Naveau, Guillaume Kon Kam King, Renaud Rincent +2
High-dimensional variable selection, with many more covariates than observations, is widely documented in standard regression models, but there are still few tools to address it in…
Inference in Gaussian state-space models with mixed effects for multiple epidemic dynamics
Romain Narci, Maud Delattre, Catherine Larédo +1
The estimation from available data of parameters governing epidemics is a major challenge. In addition to usual issues (data often incomplete and noisy), epidemics of the same natu…
A review on asymptotic inference in stochastic differential equations with mixed-effects
Maud Delattre
This paper is a survey of recent contributions on estimation in stochastic differential equations with mixed-effects. These models involve N stochastic differential equations with…
Inference for partially observed epidemic dynamics guided by Kalman filtering techniques
Romain Narci, Maud Delattre, Catherine Larédo +1
Despite the recent development of methods dealing with partially observed epidemic dynamics (unobserved model coordinates, discrete and noisy outbreak data), limitations remain in…
Estimating Fisher Information Matrix in Latent Variable Models based on the Score Function
Maud Delattre, Estelle Kuhn
The Fisher information matrix (FIM) is a key quantity in statistics as it is required for example for evaluating asymptotic precisions of parameter estimates, for computing test st…
An iterative algorithm for joint covariate and random effect selection in mixed effects models
Maud Delattre, Marie-Anne Poursat
We consider joint selection of fixed and random effects in general mixed-effects models. The interpretation of estimated mixed-effects models is challenging since changing the stru…
Estimating the number of change-points in a two-dimensional segmentation model without penalization
V. Brault, M. Delattre, E. Lebarbier +2
In computational biology, numerous recent studies have been dedicated to the analysis of the chromatin structure within the cell by two-dimensional segmentation methods. Motivated…