Challenges in model-based clustering
From MaRDI portal
Publication:6562689
DOI10.1002/wics.1248zbMATH Open1540.62018MaRDI QIDQ6562689
Publication date: 27 June 2024
Published in: Wiley Interdisciplinary Reviews. WIREs Computational Statistics (Search for Journal in Brave)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Mixture model clustering for mixed data with missing information
- Multivariate mixture modeling using skew-normal independent distributions
- Robust mixture modeling based on scale mixtures of skew-normal distributions
- Methods of moments estimation in finite mixtures
- Initializing the EM algorithm in Gaussian mixture models with an unknown number of components
- Methods for merging Gaussian mixture components
- \(\ell_{1}\)-penalization for mixture regression models
- Accounting for spot matching uncertainty in the analysis of proteomics data from two-dimensional gel electrophoresis
- Root selection in normal mixture models
- Model-based clustering for image segmentation and large datasets via sampling
- Semi-supervised model-based document clustering: a comparative study
- Choosing starting values for the EM algorithm for getting the highest likelihood in multivariate Gaussian mixture models
- Choosing initial values for the EM algorithm for finite mixtures
- Variable selection in model-based clustering: a general variable role modeling
- Finite mixture models and model-based clustering
- Inference for multivariate normal mixtures
- Estimating the dimension of a model
- Identifiability of models for clusterwise linear regression
- Time series clustering with ARMA mixtures
- Model based clustering of large data sets: tracing the development of spelling ability
- Markov chain Monte Carlo methods and the label switching problem in Bayesian mixture modeling
- Pairwise Variable Selection for High-Dimensional Model-Based Clustering
- Variable Selection for Clustering with Gaussian Mixture Models
- Consistency of the Maximum Likelihood Estimator in the Presence of Infinitely Many Incidental Parameters
- Variable Selection for Model-Based High-Dimensional Clustering and Its Application to Microarray Data
- The EM Algorithm and Extensions, 2E
- Statistical analysis of finite mixture distributions
- Discrete Parameter Variation: Efficient Estimation of a Switching Regression Model
- Algorithms for Model-Based Gaussian Hierarchical Clustering
- Model-Based Gaussian and Non-Gaussian Clustering
- Model-Based Clustering, Discriminant Analysis, and Density Estimation
- Bayesian Density Estimation and Inference Using Mixtures
- Model‐based clustering of regression time series data via APECM—an AECM algorithm sung to an even faster beat
- Efficient estimation in model‐based clustering of Gaussian regression time series
- Estimating the components of a mixture of normal distributions
- The biplot graphic display of matrices with application to principal component analysis
- Variable Selection for Model-Based Clustering
- Contributions to the mathematical theory of evolution.
Related Items (5)
Finite mixture model of hidden Markov regression with covariate dependence ⋮ Conditional mixture modelling for heavy-tailed and skewed data ⋮ A Laplace-based model with flexible tail behavior ⋮ Cluster-scaled principal component analysis ⋮ Missing values and directional outlier detection in model-based clustering
This page was built for publication: Challenges in model-based clustering
