Scientific Program and Schedule


September 3, 2014

18.00-19.00     Registration
19.00-19.30 Opening
19.30-21.00 Welcome Cocktail


September 4, 2014

08.00-08.30     Registration

08.30-09.25     Keynote Lecture 1
Sylvia Frühwirth-Schnatter
Flexible modelling based on Sparse Finite Mixtures
Chair: Angela Montanari


09.25-10.50     Talk Session 1
Model-based clustering for ordinal, categorical and mixed type data
Chair: Christian Hennig

  • Brian Francis, Fulvia Pennoni
    Improving latent class analysis through outlier detection– an example from criminal careers research
  • Monia Ranalli, Roberto Rocci
    Variable selection to clustering ordinal data through a pairwise likelihood approach
  • Yang Tang, Ryan P. Browne, Paul D. McNicholas
    Model-based clustering for the analysis of categorical data


10.50-11.20     Coffee Break


11.20-12.45     Talk Session 2
Probabilistic models for clustering
Chair: Hans-Hermann Bock

  • Hans-Hermann Bock
    Two-way clustering by maximizing a cluster-specific interactions criterion
  • Emilie Devijver
    Model-based clustering for high-dimensional regression data
  • Gunter Ritter
    Clustering heteroscedastic data


12.45-13.05     Lightning Talk Session 1
Chair: Maria Francesca Marino

  • Luis Angel García-Escudero, Alfonso Gordaliza, Francesca Greselin, Salvatore Ingrassia, Agustín Mayo-Iscar
    Robust mixtures of factor analyzers
  • Gertraud Malsiner-Walli, Sylvia Frühwirth-Schnatter, Bettina Grün
    Investigating the influence of difference priors choices for mixtures of Gaussian mixtures
  • Xavier Milhaud, Olivier Lopez
    Selection of GLM mixtures with a clustering approach
  • Paula M. Murray, Ryan P. Browne, Paul D. McNicholas
    Comparing two non-Gaussian clustering models for high-dimensional data
  • Luca Scrucca, Adrian E. Raftery
    Improved Initialisation of Model-Based Clustering Using a Gaussian Hierarchical Partition
  • Cristina Tortora, Brian C. Franczak, Ryan P. Browne, Paul D. McNicholas
    Mixtures of coalesced generalized hyperbolic distributions


13.05-14.05     Lunch


14.05-15.30     Talk Session 3
Advances in mixture models
Chair: Roberto Rocci

  • Elisabetta Bonafede, Franck Picard, Stéphane Robin, Cinzia Viroli
    Mixture of negative binomial distributions for modeling the overdispersion in RNA-SEQ data
  • Geoff McLachlan
    On Finite Mixtures of Canonical Fundamental Skew t-Distributions
  • Marco Riani, Andrea Cerioli, Francesca Torti, Domenico Perrotta
    An integrated framework for simulating mixtures of multivariate and regression data


15.30-16.25     Keynote Lecture 2
Charles Bouveyron
Discriminative variable selection in model-based clustering
Chair: Gunter Ritter


16.25-16.50     Coffee Break


16.50-18.15     Talk Session 4
Clustering models for social sciences
Chair: Brian Francis

  • Margot Bennink, Marcel A. Croon, Jeroen K. Vermunt
    Micro-macro multilevel latent class models to explain group-level outcomes using (discrete) individual-level variables
  • Leonardo Grilli, Agnese Panzera, Carla Rampichini
    Unsupervised clustering of higher level units in multilevel linear models
  • Giorgio Vittadini, Paolo Berta, Salvatore Ingrassia, Antonio Punzo
    Heterogeneity and healthcare structures effectivenes: The proposal of a cluster-weighted multilevel model


18.15-18.35     Lightning Talk Session 2
Chair: Zsuzsa Bakk

  • Marco Alfò, Maria Francesca Marino, Nikos Tzavidis
    Modelling informative missingness in longitudinal data via latent drop-out quantile regressions
  • Francesco Bartolucci, Fulvia Pennoni, Isabella Romeo
    A comparison between the latent Markov and growth mixture models for the analysis of longitudinal data
  • Francesca Bassi
    Forecasting financial products acquisition via dynamic segmentation: a comparison between standard and mixture latent class Markov models
  • Enea G. Bongiorno, Aldo Goia
    A clustering method for functional data
  • Ewa Genge
    A longitudinal study of Polish emigration attitudes using latent Markov model
  • Christina Yassouridis, Friedrich Leisch
    Analyzing Cluster Algorithms on Functional Data with Sparse Measurements


20.30     Workshop Dinner

September 5, 2014

8.45-9.40     Keynote Lecture 3
Mohamed Nadif
Document clustering under different approaches
Chair: Maurizio Vichi


9.40-10.35     Keynote Lecture 4
Francesco Bartolucci
Model selection in generalized finite mixture regression models by Hausman testing
Chair: Geoff McLachlan


10.35-11.05     Coffee Break


11.05-12.30     Talk Session 5
Recent developments in clustering models
Chair: Francesca Greselin

  • Christian Hennig
    Flexible parametric bootstrap for testing homogeneity against clustering and assessing the number of clusters
  • Silvia Liverani, Aurore Lavigne
    Quantifying partition uncertainty for Dirichlet process Bayesian clustering
  • Maurizio Vichi
    New challenges for modelling big data


12.30-12.50     Lightning Talk Session 3
Chair: Paula Murray

  • Zsuzsa Bakk, Jeroen K. Vermunt
    The robustness of bias-adjusted three-step latent class modeling with distal outcome variables
  • Gabriela Czanner, Simon Harding, Marta Garcia-Finana
    Sample size calculations for model-based supervised classification in ophthalmology
  • Angelo Mazza, Antonio Punzo, Salvatore Ingrassia
    FlexCWM: a software package for Cluster-Weighted Modeling
  • José G. C. de Souza, Francesca Torti, Marco Turchi, Matteo Negri
    Robust clustering tools for Machine Translation Quality Estimation
  • Davide Vidotto, Jeroen K. Vermunt, M.C. Kaptein
    Multiple imputation of missing categorical data through latent class models


12.50-13.50     Lunch


13.50-14.50     Talk Session 6
Supervised and unsupervised learning
Chair: Gabriela Czanner

  • Luca Frigau, Massimo Cannas, Claudio Conversano, Francesco Mola
    On the reliability of classification rules: a proposal based on the Beta regression model
  • Volodymyr Melnykov
    On model-based clustering with membership constraints


14.50-15.45     Keynote Lecture 5
Agustín Mayo-Iscar
Trimming and restrictions for model based clustering: classical approaches and new direction
Chair: Andrea Cerioli


15.45-16.45     Poster Session with Coffee Break


16.45-18.30     Talk Session 7
New developments in non-Gaussian mixture modeling
Chair: Tsung-I Lin

  • Shu-Chuan Chen
    Kimura 2-parameter ancestral mixture models for clustering DNA sequences
  • Wan-Lun Wang
    Some new tools for mixtures of common t-factor analyzers with its application
  • Min Liu, Tsung-I Lin
    Robust modeling differential effects and non-Normal distribution through mixture of skew-t regressions
  • Víctor H. Lachos Davila
    Robust mixture regression modelling based on scale mixtures of skew-normal distributions


18.30-18.40     Closing


18.40-20.00     Wine Session
Chair: Maurizio Miccichè (Calatrasi Winery)