scientific article
From MaRDI portal
Publication:2933948
zbMath1318.60078arXiv1208.4818MaRDI QIDQ2933948
Publication date: 8 December 2014
Full work available at URL: https://arxiv.org/abs/1208.4818
Title: zbMATH Open Web Interface contents unavailable due to conflicting licenses.
uniformizationGibbs samplerMCMCMarkov jump processMarkov-modulated Poisson processcontinuous-time Bayesian network
Computational methods in Markov chains (60J22) Bayesian inference (62F15) Continuous-time Markov processes on discrete state spaces (60J27)
Related Items (26)
An MCMC computational approach for a continuous time state-dependent regime switching diffusion process ⋮ Direct statistical inference for finite Markov jump processes via the matrix exponential ⋮ Bayesian state space models for dynamic genetic network construction across multiple tissues ⋮ An Exact Auxiliary Variable Gibbs Sampler for a Class of Diffusions ⋮ Efficient Parameter Sampling for Markov Jump Processes ⋮ Markov-modulated Hawkes processes for modeling sporadic and bursty event occurrences in social interactions ⋮ Bayesian inference for multistate `step and turn' animal movement in continuous time ⋮ Scalable Bayesian Multiple Changepoint Detection via Auxiliary Uniformisation ⋮ Pseudo-Marginal Inference for CTMCs on Infinite Spaces via Monotonic Likelihood Approximations ⋮ Constrained approximation of effective generators for multiscale stochastic reaction networks and application to conditioned path sampling ⋮ On the estimation of partially observed continuous-time Markov chains ⋮ Time-discretization approximation enriches continuous-time discrete-space models for animal movement ⋮ Bayesian multiple changepoints detection for Markov jump processes ⋮ Unbiased Bayesian inference for population Markov jump processes via random truncations ⋮ A hidden Markov model for decoding and the analysis of replay in spike trains ⋮ Approximation and inference methods for stochastic biochemical kinetics—a tutorial review ⋮ Stochastic epidemic models inference and diagnosis with Poisson random measure data augmentation ⋮ Variational inference for Markovian queueing networks ⋮ Bayesian inference for partially observed multiplicative intensity processes ⋮ Uncertain and negative evidence in continuous time Bayesian networks ⋮ Bottom-up learning of hierarchical models in a class of deterministic pomdp environments ⋮ Bayesian multiple changepoint detection for stochastic models in continuous time ⋮ Auxiliary variables for Bayesian inference in multi-class queueing networks ⋮ Efficient sampling of conditioned Markov jump processes ⋮ Active learning of continuous-time Bayesian networks through interventions* ⋮ Exact and computationally efficient Bayesian inference for generalized Markov modulated Poisson processes
Uses Software
This page was built for publication: