Pages that link to "Item:Q4906432"
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The following pages link to Model-Based Classification via Mixtures of Multivariate<i>t</i>-Factor Analyzers (Q4906432):
Displaying 23 items.
- Model-based classification using latent Gaussian mixture models (Q107980) (← links)
- A mixture of generalized hyperbolic factor analyzers (Q108960) (← links)
- Discussion of `Model-based clustering and classification with non-normal mixture distributions' by Lee and McLachlan (Q257613) (← links)
- Dimension reduction for model-based clustering via mixtures of multivariate \(t\)-distributions (Q369352) (← links)
- Model-based classification via mixtures of multivariate \(t\)-distributions (Q452623) (← links)
- Mixtures of modified \(t\)-factor analyzers for model-based clustering, classification, and discriminant analysis (Q622441) (← links)
- Mixtures of hidden truncation hyperbolic factor analyzers (Q779042) (← links)
- Extensions of LDA by PCA mixture model and class-wise features (Q1402670) (← links)
- Parsimonious skew mixture models for model-based clustering and classification (Q1621294) (← links)
- The joint role of trimming and constraints in robust estimation for mixtures of Gaussian factor analyzers (Q1659189) (← links)
- Clustering, classification, discriminant analysis, and dimension reduction via generalized hyperbolic mixtures (Q1659365) (← links)
- Mixtures of generalized hyperbolic distributions and mixtures of skew-\(t\) distributions for model-based clustering with incomplete data (Q1799870) (← links)
- Variational Bayes approximations for clustering via mixtures of normal inverse Gaussian distributions (Q2009044) (← links)
- Estimating parameters of mixtures of multivariate \(t\)-populations and application to classification of observations (Q2161073) (← links)
- A mixture of coalesced generalized hyperbolic distributions (Q2283312) (← links)
- On fractionally-supervised classification: weight selection and extension to the multivariate \(t\)-distribution (Q2304070) (← links)
- Factor probabilistic distance clustering (FPDC): a new clustering method (Q2418278) (← links)
- The determination of uncertainty levels in robust clustering of subjects with longitudinal observations using the Dirichlet process mixture (Q2418281) (← links)
- Capturing patterns via parsimonious \(t\) mixture models (Q2453877) (← links)
- Model-based clustering (Q2628064) (← links)
- Multivariate cluster weighted models using skewed distributions (Q2673360) (← links)
- Tilting methods for assessing the influence of components in a classifier (Q2920282) (← links)
- Unsupervised classification with a family of parsimonious contaminated shifted asymmetric Laplace mixtures (Q6546744) (← links)
