Bayesian Inference for Stochastic Kinetic Models Using a Diffusion Approximation

DOI10.1111/j.1541-0420.2005.00345.xzbMath1079.62110OpenAlexW2168282770WikidataQ51965191 ScholiaQ51965191MaRDI QIDQ5717160

Darren J. Wilkinson, Andrew Golightly

Publication date: 12 January 2006

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.1541-0420.2005.00345.x

zbMATH Keywords

Markov chain Monte Carlostochastic differential equationsnonlinear diffusionmissing datanonlinear Fokker-Planck equation

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Cell biology (92C37) Applications of Brownian motions and diffusion theory (population genetics, absorption problems, etc.) (60J70)

Related Items

Trajectory inference and parameter estimation in stochastic models with temporally aggregated data, Long-tailed graphical model and frequentist inference of the model parameters for biological networks, Direct likelihood-based inference for discretely observed stochastic compartmental models of infectious disease, A penalized simulated maximum likelihood approach in parameter estimation for stochastic differential equations, Direct statistical inference for finite Markov jump processes via the matrix exponential, Accelerating pseudo-marginal MCMC using Gaussian processes, A Bayesian estimation approach for the mortality in a stage-structured demographic model, Towards uncertainty quantification and inference in the stochastic SIR epidemic model, A penalized simulated maximum likelihood method to estimate parameters for SDEs with measurement error, Extended lasso-type MARS (LMARS) model in the description of biological network, Ensemble MCMC: accelerating pseudo-marginal MCMC for state space models using the ensemble Kalman filter, Bayesian computation methods for inference in stochastic kinetic models, Tracking hematopoietic stem cell evolution in a Wiskott-Aldrich clinical trial, Predictive inference for travel time on transportation networks, Parameter inference and model selection in deterministic and stochastic dynamical models via approximate Bayesian computation: modeling a wildlife epidemic, Reconstructing the hidden states in time course data of stochastic models, Unbiased Bayesian inference for population Markov jump processes via random truncations, Bayesian parameter inference for stochastic SIR epidemic model with hyperbolic diffusion, Approximation and inference methods for stochastic biochemical kinetics—a tutorial review, Posterior contraction rates for stochastic block models, Birth/birth-death processes and their computable transition probabilities with biological applications, Quantifying intrinsic and extrinsic noise in gene transcription using the linear noise approximation: an application to single cell data, A Rao-blackwellized particle filter for joint parameter estimation and biomass tracking in a stochastic predator-prey system, Simple simulation of diffusion bridges with application to likelihood inference for diffusions, MARS as an alternative approach of Gaussian graphical model for biochemical networks, Bayesian inference of the fractional Ornstein-Uhlenbeck process under a flow sampling scheme, Bayesian inference for functional response in a stochastic predator-prey system, Beyond the Model Limit: Parameter Inference Across Scales, Continuous-discrete smoothing of diffusions, Exact and approximate Bayesian inference for low integer-valued time series models with intractable likelihoods, Diagnostics for assessing the linear noise and moment closure approximations, Inference for reaction networks using the linear noise approximation, Loop-based conic multivariate adaptive regression splines is a novel method for advanced construction of complex biological networks, Inference of the stochastic MAPK pathway by modified diffusion bridge method, Likelihood-based inference for a class of multivariate diffusions with unobserved paths, Analysis of Markov jump processes under terminal constraints, Markovian dynamics on complex reaction networks, Local Identification of Piecewise Deterministic Models of Genetic Networks, Rate estimation in partially observed Markov jump processes with measurement errors, Moment closure based parameter inference of stochastic kinetic models, Bayesian inference for nonlinear stochastic SIR epidemic model, Bayesian inference for nonlinear multivariate diffusion models observed with error, Efficient \(\mathrm{SMC}^2\) schemes for stochastic kinetic models, A Semiautomatic Method for History Matching Using Sequential Monte Carlo, Bayesian inference for Markov jump processes with informative observations, Likelihood free inference for Markov processes: a comparison, Augmented pseudo-marginal Metropolis-Hastings for partially observed diffusion processes, Delayed acceptance particle MCMC for exact inference in stochastic kinetic models

Cites Work

• Unnamed Item
• Markov chains for exploring posterior distributions. (With discussion)
• Stochastic simulation of coupled reaction-diffusion processes
• On inference for partially observed nonlinear diffusion models using the Metropolis-Hastings algorithm
• The Calculation of Posterior Distributions by Data Augmentation
• Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models
• Likelihood Inference for Discretely Observed Nonlinear Diffusions
• Stochastic approach to chemical kinetics
• Stochastic differential equations. An introduction with applications.