Zobrazeno 1 - 10
of 99
pro vyhledávání: '"Delattre, Maud"'
Recent works have shown an interest in investigating the frequentist asymptotic properties of Bayesian procedures for high-dimensional linear models under sparsity constraints. However, there exists a gap in the literature regarding analogous theoret
Externí odkaz:
http://arxiv.org/abs/2405.01206
Latent variable models are powerful tools for modeling complex phenomena involving in particular partially observed data, unobserved variables or underlying complex unknown structures. Inference is often difficult due to the latent structure of the m
Externí odkaz:
http://arxiv.org/abs/2306.12841
Publikováno v:
Statistics and Computing, 2023, 34 (1), pp.53
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 non-linear mixed-effects models where data are collected repeatedly o
Externí odkaz:
http://arxiv.org/abs/2206.01012
Autor:
Delattre, Maud1 (AUTHOR) maud.delattre@inrae.fr, Toda, Yusuke2 (AUTHOR), Tressou, Jessica2,3 (AUTHOR), Iwata, Hiroyoshi2 (AUTHOR)
Publikováno v:
PLoS Computational Biology. 7/11/2024, Vol. 20 Issue 7, p1-26. 26p.
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 nature may be observed in several places or over different periods. The re
Externí odkaz:
http://arxiv.org/abs/2109.08428
Autor:
Delattre, Maud
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 common drift and diffusion functions but random parameters that allow
Externí odkaz:
http://arxiv.org/abs/2009.07516
Despite the recent development of methods dealing with partially observed epidemic dynamics (unobserved model coordinates, discrete and noisy outbreak data), limitations remain in practice, mainly related to the quantity of augmented data and calibra
Externí odkaz:
http://arxiv.org/abs/2007.08974
Autor:
Delattre, Maud, Kuhn, Estelle
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 statistics or asymptotic distributions in statistical testing, for evalu
Externí odkaz:
http://arxiv.org/abs/1909.06094
Autor:
Delattre, Maud, Poursat, Marie-Anne
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 structure of one set of effects can lead to different choices of important
Externí odkaz:
http://arxiv.org/abs/1612.02405
Publikováno v:
In Computational Statistics and Data Analysis December 2021 164