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March 2012

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From:
Christian Hennig <[log in to unmask]>
Reply To:
Classification, clustering, and phylogeny estimation
Date:
Mon, 26 Mar 2012 20:51:22 +0100
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CSDA 2nd Special Issue on ADVANCES IN MIXTURE MODELS

COMPUTATIONAL STATISTICS AND DATA ANALYSIS
CALL FOR PAPERS
2nd Special Issue on ADVANCES IN MIXTURE MODELS
http://www.elsevier.com/locate/csda

http://www.compstat2012.org/SpecialIssues/Mixture2011.pdf

We are inviting submissions for a special issue of Computational
Statistics and Data Analysis dealing with Advances in Mixture Models.

Mixture models experience sustainable popularity over recent years.
Not only that they are natural models to adjust for unobserved or
latent heterogeneity, they are fundamental cornerstones in many areas
in statistics such as smoothing, empirical Bayes, likelihood based
clustering, or latent variable analysis among others.  As
semi-parametric models they embody an excellent compromise in the
trade-off between imposed model structure and freedom in model
adaptation to the data. However, mixture models experience a number of
difficulties. The likelihood may not be bounded, and, even if it were,
the global maximum might not be a good choice. Algorithmic solutions
are nearly almost required and algorithms such as the EM algorithm is
experiencing numerous problems such as the choice of initial values or
using an adequate stopping rule. The number of components problem and
model selection add one more to the many areas of interest. Diverse
application areas such as capture-rapture approaches or clustering of
gene expression data have been added to numerous existing application
areas such as disease mapping or meta-analysis. There is also a
growing body of work on mixtures of (generalised) regression models.
Topics of interest include, but are not limited to, the following:

Key areas are:

Algorithms: Starting and Stopping Rules
Testing in Mixture Models
Mixtures with Unbounded Likelihoods
Identifiability Problems
Multivariate Mixtures
Robustness of Mixture Estimation
Mixture Models for Clustering
Mixtures of (Generalized) Linear Models
Problems in Bayesian Approaches for Mixtures
Mixtures of Parametric Mixtures
Mixtures of Profile Likelihoods
Free Topics dealing with Mixtures

The papers should have a computational or advanced data analytic
component in order to be considered for publication.  Authors who are
uncertain about the suitability of their papers should contact the
special issue editors. All submissions must contain original
unpublished work not being considered for publication elsewhere.

Submissions will be refereed according to standard procedures for
Computational Statistics & Data Analysis. Information about the
journal can be found at http://www.elsevier.com/locate/csda.

The deadline for submissions is *30 June 2012*.  However, papers can
be submitted at any time; and, when they have been received, they will
enter the editorial system immediately.

Papers for the special issue should be submitted using the Elsevier
Electronic Submission tool EES: http://ees.elsevier.com/csda. In the
EES please choose the special issue on "Advances on Mixture
Models" and the Co-Editor responsible for the special issues.

The special issue editors:

Dankmar Bohning, University of Southampton, UK.
E-mail: [log in to unmask]

Christian Hennig, University College London, UK.
E-mail: [log in to unmask]

Geoff McLachlan,  University of Queensland, Australia.
E-mail: [log in to unmask]

Paul McNicholas, University of Guelph, Canada.
E-mail: [log in to unmask]

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