WORKSHOP IN

STATISTICAL MIXTURES AND LATENT-STRUCTURE MODELLING


International Centre for Mathematical Sciences,
Edinburgh,   March 28 - March 30,  2001

Oganizers  C.P. Robert (Paris) and D.M. Titterington  (Glasgow)
 

Picture of Edinburgh castle from Edinburgh - Scotland's Capital Citygh - Scotland's Capital City
 



| Purpose of the workshop | Background| Current trends | Speakers| Structure of the Workshop | References

Purpose of the workshop


This is a three-day workshop, held at the International Centre for Mathematical Sciences (ICMS) with 45participants, funded by the EPSRC and supported by the Research Section of the Royal Statistical Society.

The motivation for the Workshop is the awareness that the topic of mixture modelling and the wider versions that constitute latent structure analysis are currently of major interest to an increasingly wide range of scientific disciplines. The following are likely to be major sub-topics, although the field is a fast-moving one:

Background


Until the last five years or so, the theory and methodology of mixture distributions were of interest mainly to statisticians, although there was a substantial amount of work in the engineering and speech-modelling literatures concerning the closely related but technically more complicated version known as hidden Markov modelling. The fields of application in which mixture models have been found relevant have however been extremely diverse, throughout science, medicine, engineering and even the humanities. So far as other manifestations of latent structure are concerned, such as latent class analysis and factor analysis, the methodological development and much of the applications have traditionally been associated with statistical researchers specialising in the social sciences. In general with all these types of model, methodology and theory have developed steadily over a period of about 100 years, since Karl Pearson first wrote about mixtures in 1894, but the field has recently exploded in activity, thanks mainly to the following events:

Current trends

Speakers and Participants


The Workshop has now reached its maximal audience size

The list of speakers and talks is as follows:
 

M. Aitkin                'Likelihood and Bayesian analysis of mixture models'
C. Andrieu              `SAME, SA^2ME, FAME and RDA'
C.M. Bishop          'Variational methods and latent variables'
G. Celeux                'Assessing the number of mixture components: a survey'
P. Dellaportas        'Latent variables for modelling volatility processes'
E. Gassiat               'The number of populations in a mixture with Markov regime'
P.J. Green                `Mixtures in time and space'
G. Hinton                'Products of mixtures'
B.G. Lindsay          'On determining an adequate number of mixture components'
N.L. Hjort               'On attempts at generalising the Dirichlet process'
D.J.C. MacKay       'The state of the art in error correcting codes'
G.J. McLachlan      'On the Incremental EM Algorithm for Speeding Up the Fitting of Finite Mixture Models'
E. Moulines              ` Maximum likelihood estimation for non-linear autoregressive processes with Markov regime'
R. Neal                       'Hierarchical mixtures using diffusion tree priors'
C. Robert            'Where do we stand on mixtures'
G.O. Roberts     'Bayesian inference for discretely observed diffusion processes'
T. Ryden                   `Continuous-time jump MCMC and model selection for HMMs'
C. Skinner                 'Estimation of distributions in the presence of measurement error'
M. Stephens              'Inferring latent population structure from genetic data '
M. Titterington     `Stock taking discussion'
C.K.I. Williams       'Image modelling with dynamic trees'
 
 

Picture of the Aonach Eagach ridge from Glencoe Mountain Sport


Structure of the Workshop


Although many of the proposed participants are very distinguished,  many will not give a formal presentation. We prefer a comparatively small number of longish talks rather than many short presentations. However  everyone has the opportunity to communicate his/her research by reserving some specific periods for one poster session and by organising these sessions in such a way that everyone attends, as in the Valencia Bayesian meetings.


Previsional Schedule

Wenesday, March 28

  900 - 1000     Registration

1000 - 1100     C.P. Robert [abstract]

1100 - 1130     Coffee

1130 - 1250     M. Aitkin [abstract] and C.Skinner

1250 - 1420     Lunch

1420 - 1540     M.Stephens and P.J. Green

1540 - 1610    Tea

1610 - 1730     P. Dellaportas and G. Roberts

1730 - 1900     Wine and cheese reception
 

Thursday, March 29

    0930 - 1050    E. Moulines  [abstract]  and N. Hjort

   1050 - 1120   Coffee

   1120 - 1240     G. Hinton and C.M. Bishop

   1240 - 1400   Lunch

   1400 - 1600   R. Neal  [abstract] , C.K.I. Williams and D.J.C.  MacKay

   1600 - 1630   Tea

   1615 - 1800    Posters  [list]

   1930           Optional dinner
 

Friday, March 30


    0930 - 1050    G. McLachlan and C. Andrieu  (abstract)

   1050 - 1120   Coffee

   1120 - 1240     E. Gassiat and  D. Lindsay

   1240 - 1400   Lunch

   1400 - 1520     T. Ryden and  G. Celeux

   1520 - 1540   Tea

   1540 - 1630    D.M. Titterington
 
 

Picture of Whitemount on Rannoch Moor taken by Paul Dobbie
 


Note: There is another meeting on mixture theory and applications, Mixtures 2001,
organised by D. Bohning and W. Seidel in Hamburg, 23 - 28 July 2001. See here for more details.


References

Berger, J.O. & Perrichi, L. (1996) J. Am. Statist. Assoc. 91 109-122.
Böhning, D. (1999) Computer-Assisted Analysis of Mixtures and Applications. Chapman and Hall
Carlin, B. & Chib, S. (1995) J.R. Statist. Soc. B 57, 473-484.
Celeux, G., Hurn, M. & Robert, C.P. (2000) J. Am. Statist. Assoc. (to appear)
Geman, S & Geman, D. (1984) IEEE Trans. PAMI 6, 721-741.
Green, P.J. (1995) Biometrika 82, 411-732.
Jordan, M.I. (Ed.) (1999) Learning in Graphical Models. MIT Press.
Jordan, M.I. & Jacobs, R.A. (1994) Neural Computation6, 181-214.
Kass, R.E. & Raftery, A.E. (1995) J. Am. Statist. Assoc. 90, 773-795.
Lindsay, B.G. (1995) Mixture models: Theory, Geometry and Applications. IMS
McLachlan, G.J. (1987) Appl. Statist. 36, 318-324.
Mengersen, K.L. & Robert, C.P. (1996) In Bayesian Statistics 5, 255-276. OUP
Møeller, J., Mira, A. & Roberts, G.O. (1999) Preprint.
Moreno, E. & Liseo, B. (1998) Preprint
O'Hagan, A. (1995) J.R. Statist. Soc. B 57, 99-138.
Petrone, S. (1999) Canadian J. Statist. 27, 105-126
Phillips, D.B. & Smith, A.F.M. (1996) In MCMC in Practice, 215-240. Chapman and Hall.
Raftery, A.E. (1996) In MCMC in Practice, 163-188. Chapman and Hall
Richardson, S. & Green, P.J. (1997) J.R. Statist. Soc. B 59, 731-792.
Roeder, K. & Wasserman, L. (1997) J. Am. Statist. Assoc. 92, 894-902.
Stephens, M. (1998). D.Phil. Thesis, Oxford University.



| Purpose of the workshop | Background| Current trends | Speakers| Structure of the Workshop | References
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