Image de couverture de livre

Posterior contraction rates in a sparse non-linear mixed-effects model

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Naveau, Marion, Delattre, Maud, Sansonnet, Laure
Format:	Preprint
Publié:	2024
Sujets:	Statistics Theory
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Bayesian high-dimensional covariate selection in non-linear mixed-effects models using the SAEM algorithm
par: Naveau, Marion, et autres
Publié: (2022)

Quasi-likelihood inference for SDE with mixed-effects observed at high frequency
par: Delattre, Maud, et autres
Publié: (2025)

Online and Offline Robust Multivariate Linear Regression
par: Godichon-Baggioni, Antoine, et autres
Publié: (2024)

ERM-Lasso classification algorithm for Multivariate Hawkes Processes paths
par: Dion-Blanc, Charlotte, et autres
Publié: (2024)

Gaussian quasi-likelihood analysis for non-Gaussian linear mixed-effects model with system noise
par: Imamura, Takumi, et autres
Publié: (2024)

Posterior contraction under misspecification and heteroscedasticity in non-linear inverse problems
par: Seizilles, Fanny, et autres
Publié: (2026)

Posterior contraction and uncertainty quantification for the multivariate spike-and-slab LASSO
par: Shen, Yunyi, et autres
Publié: (2022)

Detection and inference of changes in high-dimensional linear regression with non-sparse structures
par: Cho, Haeran, et autres
Publié: (2024)

Uniform inference in linear mixed models
par: Ekvall, Karl Oskar, et autres
Publié: (2025)

Empirical Bayes inference in sparse high-dimensional generalized linear models
par: Tang, Yiqi, et autres
Publié: (2023)

Multi-block linearized alternating direction method for sparse fused Lasso modeling problems
par: Wu, Xiaofei, et autres
Publié: (2023)

On strong posterior contraction rates for Besov-Laplace priors in the white noise model
par: Dolera, Emanuele, et autres
Publié: (2024)

A note on the minimax risk of sparse linear regression
par: Guo, Yilin, et autres
Publié: (2024)

Multivariate extreme value theory
par: Naveau, Philippe, et autres
Publié: (2024)

Signal-to-noise ratio aware minimax analysis of sparse linear regression
par: Ghosh, Shubhangi, et autres
Publié: (2025)

A Kullback-Leibler divergence test for multivariate extremes: theory and practice
par: Engelke, Sebastian, et autres
Publié: (2026)

Restricted maximum likelihood estimation in generalized linear mixed models
par: Maestrini, Luca, et autres
Publié: (2024)

Heavy-tailed and Horseshoe priors for regression and sparse Besov rates
par: Agapiou, Sergios, et autres
Publié: (2025)

Contraction rates for sparse variational approximations in Gaussian process regression
par: Nieman, Dennis, et autres
Publié: (2021)

A minimax optimal approach to high-dimensional double sparse linear regression
par: Zhang, Yanhang, et autres
Publié: (2023)

Adaptive posterior concentration rates for sparse high-dimensional linear regression with random design and unknown error variance
par: Mai, The Tien
Publié: (2024)

$L^2-$posterior contraction rates for Gaussian process and random series priors in Bayesian nonparametric regression models
par: Rosa, Paul
Publié: (2025)

On the effect of noise on fitting linear regression models
par: Ullah, Insha, et autres
Publié: (2024)

A closed form solution for Bayesian analysis of a simple linear mixed model
par: Vinje, Hilde, et autres
Publié: (2026)

Maximum likelihood estimation in the sparse Rasch model
par: Peng, Pai, et autres
Publié: (2025)

Posterior consistency in multi-response regression models with non-informative priors for the error covariance matrix in growing dimensions
par: Sarkar, Partha, et autres
Publié: (2023)

Posterior Contraction rate and Asymptotic Bayes Optimality for one-group shrinkage priors in sparse normal means problem
par: Paul, Sayantan, et autres
Publié: (2022)

A log-linear model for non-stationary time series of counts
par: Leucht, Anne, et autres
Publié: (2023)

Conditional bootstrap for non-linear mixed effects models
par: Kaisaridi, Sofia, et autres
Publié: (2026)

Estimation and variable selection in high dimension in nonlinear mixed-effects models
par: Caillebotte, Antoine, et autres
Publié: (2025)

Proper Scoring Rules for Multivariate Probabilistic Forecasts based on Aggregation and Transformation
par: Pic, Romain, et autres
Publié: (2024)

Necessary and sufficient conditions for posterior propriety for generalized linear mixed models
par: Rao, Yalin, et autres
Publié: (2023)

Learning sparse generalized linear models with binary outcomes via iterative hard thresholding
par: Matsumoto, Namiko, et autres
Publié: (2025)

Minimax estimation of functionals in sparse vector model with correlated observations
par: Wang, Yuhao, et autres
Publié: (2024)

On the contraction rate of the posterior distribution for nonlinear PDE parameter identification
par: Fan, Yuxin, et autres
Publié: (2026)

Posterior inference via Hill's prediction model
par: Bissiri, Pier Giovanni, et autres
Publié: (2026)

$L_2$-norm posterior contraction in Gaussian models with unknown variance
par: Jeong, Seonghyun
Publié: (2025)

Penalized spline estimation of principal components for sparse functional data: rates of convergence
par: He, Shiyuan, et autres
Publié: (2024)

Exact recovery in the double sparse model: sufficient and necessary signal conditions
par: Liu, Shixiang, et autres
Publié: (2025)

Tree-based conditional copula estimation
par: Bonacina, Francesco, et autres
Publié: (2024)