Rate estimation in partially observed Markov jump processes with measurement errors
From MaRDI portal
Publication:746231
DOI10.1007/s11222-011-9244-1zbMath1322.62096arXiv1008.5246OpenAlexW2042382417MaRDI QIDQ746231
Michael Amrein, Hans R. Künsch
Publication date: 16 October 2015
Published in: Statistics and Computing (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1008.5246
Bayesian inferenceMarkov chain Monte Carlo methodsparticle filterMarkov jump processstochastic kineticsgeneral state space model
Lua error in Module:PublicationMSCList at line 37: attempt to index local 'msc_result' (a nil value).
Related Items (3)
Inference for reaction networks using the linear noise approximation ⋮ Inverse Gillespie for inferring stochastic reaction mechanisms from intermittent samples ⋮ Sequential Bayesian inference in hidden Markov stochastic kinetic models with application to detection and response to seasonal epidemics
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Simulation from endpoint-conditioned, continuous-time Markov chains on a finite state space, with applications to molecular evolution
- Bayesian inference for nonlinear multivariate diffusion models observed with error
- Following a Moving Target—Monte Carlo Inference for Dynamic Bayesian Models
- Sequential Monte Carlo Methods in Practice
- On Lewis' simulation method for point processes
- Exact Filtering for Partially Observed Continuous Time Models
- Bayesian Inference for Stochastic Kinetic Models Using a Diffusion Approximation
This page was built for publication: Rate estimation in partially observed Markov jump processes with measurement errors