Parameter Estimation Using the EM Algorithm for Symmetric Stable Random Variables and Sub-Gaussian Random Vectors.
Mahdi TeimouriSaeid RezakhahAdel MohammadpourPublished in: J. Stat. Theory Appl. (2018)
Keyphrases
- random vectors
- parameter estimation
- em algorithm
- random variables
- maximum likelihood
- marginal distributions
- expectation maximization
- gaussian mixture
- gaussian mixture model
- random fields
- normal distribution
- graphical models
- probability distribution
- mixture model
- maximum likelihood estimation
- gaussian distribution
- joint distribution
- generative model
- conditional independence
- likelihood function
- hyperparameters
- hidden variables
- bayesian networks
- latent variables
- approximate inference
- probability density function
- probabilistic model
- conditional probabilities
- parameter learning
- gibbs sampling
- posterior distribution
- maximum a posteriori
- belief propagation
- density estimation
- bayesian model selection
- maximum likelihood estimates
- markov property
- machine learning
- markov chain monte carlo
- structure learning
- model selection
- image segmentation
- computer vision