Monte Carlo EM algorithm for two-component mixture of generalized linear random effects models with varying coefficients.
Xingcai ZhouChangchun TanPublished in: EMEIT (2011)
Keyphrases
- monte carlo
- em algorithm
- expectation maximization
- mixture model
- finite mixture model
- parameter estimation
- random effects
- probabilistic model
- gaussian mixture model
- exponential family
- generalized linear
- maximum likelihood
- hidden variables
- log likelihood
- incomplete data
- markov chain
- maximum likelihood estimation
- generative model
- probability density function
- image segmentation
- density estimation
- markov chain monte carlo
- model selection
- bayesian framework
- gaussian distribution
- particle filter
- maximum a posteriori
- hyperparameters
- random fields
- latent variables
- unsupervised learning
- multiscale
- feature extraction