Particle methods for stochastic differential equation mixed effects models
From MaRDI portal
Publication:2057332
DOI10.1214/20-BA1216zbMath1480.62053arXiv1907.11017OpenAlexW3036062512WikidataQ115240796 ScholiaQ115240796MaRDI QIDQ2057332
Publication date: 6 December 2021
Published in: Bayesian Analysis (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1907.11017
Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10)
Related Items (5)
A review on asymptotic inference in stochastic differential equations with mixed effects ⋮ Sequentially guided MCMC proposals for synthetic likelihoods and correlated synthetic likelihoods ⋮ Automatically adapting the number of state particles in \(\text{SMC}^2\) ⋮ Particle methods for stochastic differential equation mixed effects models ⋮ Score-Based Parameter Estimation for a Class of Continuous-Time State Space Models
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Bayesian Synthetic Likelihood
- Zero variance Markov chain Monte Carlo for Bayesian estimators
- The pseudo-marginal approach for efficient Monte Carlo computations
- The Correlated Pseudo-Marginal Method
- A general framework for the parametrization of hierarchical models
- Exploiting multi-core architectures for reduced-variance estimation with intractable likelihoods
- On some properties of Markov chain Monte Carlo simulation methods based on the particle filter
- Efficient inference for stochastic differential equation mixed-effects models using correlated particle pseudo-marginal algorithms
- Practical estimation of high dimensional stochastic differential mixed-effects models
- Bayesian inference for nonlinear multivariate diffusion models observed with error
- A hierarchical Ornstein-Uhlenbeck model for continuous repeated measurement data
- Bayesian inference for diffusion-driven mixed-effects models
- Improved bridge constructs for stochastic differential equations
- Randomized quasi-Monte Carlo: an introduction for practitioners
- Particle methods for stochastic differential equation mixed effects models
- Negative association, ordering and convergence of resampling methods
- Computationally efficient Bayesian estimation of high-dimensional Archimedean copulas with discrete and mixed margins
- On the efficiency of pseudo-marginal random walk Metropolis algorithms
- Bayesian inference for irreducible diffusion processes using the pseudo-marginal approach
- Bayesian Analysis of Growth Curves Using Mixed Models Defined by Stochastic Differential Equations
- Stochastic Differential Mixed-Effects Models
- Particle Markov Chain Monte Carlo for Efficient Numerical Simulation
- Sequential Monte Carlo Samplers
- Nonparametric spline regression with prior information
- Maximum Likelihood Estimation for Stochastic Differential Equations with Random Effects
- Multivariate output analysis for Markov chain Monte Carlo
- Efficient implementation of Markov chain Monte Carlo when using an unbiased likelihood estimator
- Modeling space-time data using stochastic differential equations
This page was built for publication: Particle methods for stochastic differential equation mixed effects models
