The following pages link to Emmixuskew (Q28219):
Displaying 21 items.
- A mixture of generalized hyperbolic factor analyzers (Q108960) (← links)
- A general class of scale-shape mixtures of skew-normal distributions: properties and estimation (Q154852) (← links)
- Manly transformation in finite mixture modeling (Q158374) (← links)
- Model-based clustering and classification with non-normal mixture distributions (Q257605) (← links)
- On nomenclature for, and the relative merits of, two formulations of skew distributions (Q273733) (← links)
- Comment on ``On nomenclature, and the relative merits of two formulations of skew distributions'' by A. Azzalini, R. Browne, M. Genton, and P. McNicholas (Q297127) (← links)
- Extending mixtures of factor models using the restricted multivariate skew-normal distribution (Q900823) (← links)
- Black-Litterman model for continuous distributions (Q1622823) (← links)
- Location and scale mixtures of Gaussians with flexible tail behaviour: properties, inference and application to multivariate clustering (Q1663203) (← links)
- Objective Bayesian analysis for the multivariate skew-\(t\) model (Q1663612) (← links)
- A comparison of the \(L_2\) minimum distance estimator and the EM-algorithm when fitting \(k\)-component univariate normal mixtures (Q1685303) (← links)
- Mixture model modal clustering (Q1999447) (← links)
- Finite mixtures of multivariate scale-shape mixtures of skew-normal distributions (Q2029226) (← links)
- An overview of skew distributions in model-based clustering (Q2062796) (← links)
- Investigation of parameter uncertainty in clustering using a Gaussian mixture model via jackknife, bootstrap and weighted likelihood bootstrap (Q2282602) (← links)
- A mixture of coalesced generalized hyperbolic distributions (Q2283312) (← links)
- Hidden truncation hyperbolic distributions, finite mixtures thereof, and their application for clustering (Q2404418) (← links)
- Unifying data units and models in (co-)clustering (Q2418082) (← links)
- The Mixturegram: A Visualization Tool for Assessing the Number of Components in Finite Mixture Models (Q3391089) (← links)
- Variable Selection for Skewed Model-Based Clustering: Application to the Identification of Novel Sleep Phenotypes (Q4690931) (← links)
- An Introduction to Clustering with R (Q5119497) (← links)
