A Mixture of Coalesced Generalized Hyperbolic Distributions

No abstract is available for this paper.

• Publication year

  2014

• Venue

  Journal of Classification

• Publication date

  2014-03-10

• Fields of study

  Mathematics, Computer Science

• Identifiers
  DOI 10.1007/s00357-019-09319-3
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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  2005influential reference
• Absolute Moments of Generalized Hyperbolic Distributions and Approximate Scaling of Normal Inverse Gaussian Lévy Processes

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• The EM algorithm and extensions

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• Bayesian Density Estimation and Inference Using Mixtures

  1995cited by this paper
• Mixture models : theory, geometry, and applications

  1995cited by this paper
• Continuous Univariate Distributions.

  1995influential reference
• Gaussian parsimonious clustering models

  1995cited by this paper
• The distribution of the likelihood ratio for mixtures of densities from the one-parameter exponential family

  1994cited by this paper
• An Introduction to Regression Graphics

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