Bayesian Parameter Estimation for Stochastic Reaction Networks from Steady-State Observations.
Ankit GuptaMustafa KhammashGuido SanguinettiPublished in: CMSB (2019)
Keyphrases
- parameter estimation
- steady state
- maximum likelihood
- posterior distribution
- state dependent
- markov chain
- bayesian model selection
- model selection
- least squares
- product form
- markov random field
- operating conditions
- random fields
- markov chain monte carlo
- steady states
- em algorithm
- explicit expressions
- queueing networks
- queue length
- expectation maximization
- genetic regulatory networks
- queueing model
- bayesian networks
- parameter estimation algorithm
- fluid model
- arrival rate
- heavy traffic
- service times
- posterior probability
- bayesian inference
- parameter estimates
- approximate inference
- structure learning
- biological networks
- network structure
- hyperparameters
- markov fields
- traffic intensity
- higher order
- reinforcement learning