Recent developments in expectation-maximization methods for analyzing complex data
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Publication:6607911
DOI10.1002/wics.1277zbMath1545.62108MaRDI QIDQ6607911
Publication date: 19 September 2024
Published in: Wiley Interdisciplinary Reviews. WIREs Computational Statistics (Search for Journal in Brave)
Cites Work
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- Longitudinal data analysis using generalized linear models
- Simultaneous model-based clustering and visualization in the Fisher discriminative subspace
- Analytic calculations for the EM algorithm for multivariate skew-\(t\) mixture models
- Initializing the EM algorithm in Gaussian mixture models with an unknown number of components
- Handbook of computational statistics. Concepts and methods.
- A marginal regression model for multivariate failure time data with a surviving fraction
- Finite mixtures of multivariate skew \(t\)-distributions: some recent and new results
- The MM alternative to EM
- Choosing starting values for the EM algorithm for getting the highest likelihood in multivariate Gaussian mixture models
- A weakly informative default prior distribution for logistic and other regression models
- On the convergence properties of the EM algorithm
- Another interpretation of the EM algorithm for mixture distributions
- EM algorithms for Gaussian mixtures with split-and-merge operation.
- Mixture models for clustering multilevel growth trajectories
- Speeding up the EM algorithm for mixture model-based segmentation of magnetic resonance images
- Acceleration of the EM algorithm: P-EM versus epsilon algorithm
- On-Line Expectation–Maximization Algorithm for latent Data Models
- Mixtures
- Imputing unobserved values with the EM algorithm under left and right-truncation, and interval censoring for estimating the size of hidden populations
- Maximum likelihood estimation via the ECM algorithm: A general framework
- Two slice-EM algorithms for fitting generalized linear mixed models with binary response
- The EM Algorithm and Extensions, 2E
- Maximizing Generalized Linear Mixed Model Likelihoods With an Automated Monte Carlo EM Algorithm
- The ECME algorithm: A simple extension of EM and ECM with faster monotone convergence
- A new class of multivariate skew distributions with applications to bayesian regression models
- A Correlated Probit Model for Joint Modeling of Clustered Binary and Continuous Responses
- A Joint Model for Nonlinear Mixed-Effects Models With Censoring and Covariates Measured With Error, With Application to AIDS Studies
- Mixtures of marginal models
- ECM algorithms that converge at the rate of EM
- Finite mixture models
- Importance of replication in microarray gene expression studies: Statistical methods and evidence from repetitive cDNA hybridizations
- A Nonparametric Mixture Model for Cure Rate Estimation
- Maximum likelihood multiple-source localization using acoustic energy measurements with wireless sensor networks
- The Dynamic ‘Expectation–Conditional Maximization Either’ Algorithm
- Unsupervised learning by probabilistic latent semantic analysis
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