Bayesian covariance matrix estimation using a mixture of decomposable graphical models.
Helen ArmstrongChristopher K. CarterKin Foon Kevin WongRobert KohnPublished in: Stat. Comput. (2009)
Keyphrases
- graphical models
- covariance matrix
- markov networks
- covariance matrices
- multivariate gaussian
- bayesian networks
- class conditional densities
- estimation error
- gaussian mixture
- maximum likelihood
- belief propagation
- probabilistic model
- random variables
- statistical inference
- probabilistic graphical models
- maximum likelihood estimation
- sample size
- exponential family
- posterior probability
- conditional random fields
- approximate inference
- mixture model
- principal component analysis
- bayesian inference
- parameter estimation
- mahalanobis distance
- conditional independence
- graph structure
- gaussian distribution
- maximum margin
- density estimation
- expectation maximization
- correlation matrix
- objective function
- gaussian processes
- semi supervised