The deadline of submissions is the 21st of May 2005.
World Conference on Computational Statistics & Data Analysis
Amathus Beach Hotel, Limassol, Cyprus, 28-31 October, 2005
http://www.csdassn.org/europe/csda2005/
The 3rd International Association for Statistical Computing (IASC)
world conference on Computational Statistics and Data Analysis will
take place at the Amathus Beach Hotel in Limassol, Cyprus, October
28-31, 2005.
The conference aims at bringing together researchers and practitioners
to discuss recent developments in computational methods, methodology
for data analysis and applications in statistics. It is associated
with the Computational Statistics and Data Analysis (CSDA), the
official journal of the IASC. This is an international journal
dedicated to the dissemination of methodological research and
applications in the areas of computational statistics and data
analysis (URL: http://www.elsevier.com/locate/csda).
The IASC Conference consists of a number of topics (tracks) with their
own "Call For Papers" and Chairs (see list below). Papers that are
within the scope and aims of the CSDA Journal are solicited.
o The deadline for submissions of 1-page abstracts is May 21, 2005.
o Decisions will be made by May 28th, 2005.
o Peer review papers will be considered for publication in thematic
special issues of the journal Computational Statistics and Data
Analysis.
More details can be found in the web page of the conference:
http://www.csdassn.org/europe/csda2005/
List of tracks and chairs:
T01: Functional Genomics: Computational and Statistical Aspects
A. Benner, R. Gentleman, G. McLachlan and M. Mittlbock
T02: Robust and Nonparametric Methods
R. Wilcox, S. Sheather and E. Brunner
T03: Model Selection, Computational Methods, and Optimization
Heuristics
H. Bozdogan, M. Gilli and P. Winker
T04: Applications in Macro-Economics, Finance and Marketing
P.J.F. Groenen and H. van Dijk
T05: Computer-intensive methods for dependent data
Q. Yao, M. La Rocca, R. Chen and D.N. Politis
T06: Statistical Learning Methods involving Dimensionality Reduction
H.-H. Bock, T. Hastie and M. Vichi
T07: Clinical Trials
M. Neuhauser, F.C. Lam, J. Niland and N. Victor
T08: Statistics for Functional data
W.G. Manteiga and P. Vieu
T09: Machine Learning and Scientific Computing
H. Zha, C. Ding, M. Ng and E. Gallopoulos
T10: Robust data mining
C. Croux, R. Zamar, P. Filzmoser and S. Van Aelst
T11: Latent Variable and Structural Equation Models
I. Moustaki and S.-Y. Lee
T12: Statistical Signal Extraction and Filtering
D.S.G. Pollock and T. Proietti
T13: Advances in Mixture Models
D. Bohning, W. Seidel, B. Garel, V. Patilea, G. McLachlan,
M. Alfo and M. Greiner
T14: Visualization methods for analyzing large data sets
A. Wilhelm, C.-H. Chen and E.J. Wegman
T15: Mixed models for Complex and Large Problems
R. Payne and B.R. Cullis
T16: Nonlinear time series modelling
A. Amendola, S.J. Koopman, C. Francq and W.-S. Chan
T17: Financial econometrics
S. J. Koopman, G. Barone-Adesi, M. Ooms, A. Amendola and
E.Zivot
T18: Flexible function estimation in high dimensional problems
M.G. Schimek, I. Horova and D.W. Scott
T19: New developments in software for statistical computing
M.H., J. Nakano and A. Unwin
T20: Models and methods for Customer Relationship Management
G. Saporta, G. Giordano and H. Wang
T21: Recursive Partitioning and related methods
R. Siciliano, J.J. Meulman and .Conversano
T22: Partial Least Squares: A Framework for Data Analysis and
Statistical Modeling
C. Lauro, V.E. Vinzi, W.W. Chin and A. Phatak
T23: Fuzzy Statisitcal Analysis
R. Coppi and M. Angeles
T24: Computational Econometrics
D. Belsley, E.J. Kontoghiorghes, J. Magnus and P. Foschi
T25: Statistical Algorithms and Software
J. Gentle, J. Hinde and C. Gatu
T26: Matrices and Statistics
B. Philippe, J.L. Barlow and E.J. Kontoghiorghes
T27: Analysis of Symbolic and Structured Data
P. Brito, L. Billard, E. Diday, G. Hebrail and D.Malerba
|