SYMPOSIUM ON LARGE DATA SETS
November 6th., 2003
Amsterdam, The Netherlands
http://www.vvs-ssp.nl/symposium2003.html


Organization
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Section Statistical Software of The Netherlands Society for
Statistics and Operations Research


Program Committee
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Dr. Ruud Koning, Universiteit of Groningen
Prof.dr. Arno Siebes, University of Utrecht
Dr. Siem Heisterkamp, National Institute of Public Health and
the Environment (RIVM)
Prof.dr. Patrick Groenen, Erasmus University Rotterdam


Large Data Sets
________________________________
Fifteen years ago, handling of large datasets, let alone
analysis in them was a nearly impossible task for researchers.
The data were often stored on tape, and even the process of
reading the dataset into the memory of a mainframe was slow.
Memory was scarce, and so it was difficult to save intermediate
results. Such datasets were analyzed using either tailor-made
statistical software, or self-written programs using routines
from numerical libraries like NAG or IMSL. Maximum-likelihood
estimation of non-linear models was non-trivial if not
impossible, and researchers often had to be satisfied with
one-step improvements over some consistent estimator.

Things have changed for the better, from a technical point of
view.  Huge datasets are routinely available to researchers in
different fields, like finance, marketing, biomedical sciences,
particle physics, astronomy, life sciences, and social
sciences. Datasets used to be large in the sense of containing
many observations on a small number of variables. But nowadays,
e.g. in the life sciences we are confronted with datasets with
a small number of observations and a huge number of variables.
Data can be transported on media that can be read by most
personal computers, and the computing power on the desk of a
statistical researcher is absolutely impressive. Instead of
focusing on the mechanics of the analysis of datasets,
researchers can focus on the actual statistical analysis. Thus
the question has turned into: Now that we have a lot of data,
what could we do with it?

This conference addresses the analysis of very large datasets,
both from the point of view of a statistician who works with
such datasets as well as the point of view of practitioners
from various fields. By presenting several applications and
tools available to a modern day statistical researcher, we want
to show that large datasets offer unique opportunities for
researchers to answer questions that were difficult to tackle
before. The program committee is delighted to be able to
present a selection of the top researchers on this topic.


Program
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9:30  registration and coffee
10:00  opening
10:05  Yoav Benjamini
       Tel-Aviv University
       Multiplicity issues related to complex research questions
       in microarrays analysis
10:55  Philip Hans Franses
       Erasmus University, Rotterdam
       More, but also better?
11:40  Paul Eilers
       Leiden University Medical Centre
       Low Memory, High Speed Smoothing on Large
       Multidimensional Grids
12:30  Lunch
13:30  Andreas Buja
       University of Pennsylvania
       Hands-On Experiences with Mining Telecom Data
14:15  Jos Roerdink
       University of Groningen
       Visualization of large data sets with applications in
       life science
15:00  coffee/ tea break
15:15  Geert Wets
       Limburg University, Belgium
       Large data sets in traffic safety
16:30  Drinks


Registration
________________________________
Please register via email to [log in to unmask] or online via:
http://www.vvs-ssp.nl/symposium2003registration.html

VVS-SSP
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1055 RX  Amsterdam
The Netherlands

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Our Sponsors
________________________________
CANdiensten
Your Partner in Mathematics and Statistics
Nieuwpoortkade 23-25
1055 RX Amsterdam
The Netherlands
http://www.candiensten.nl/english

SAS Institute B.V.
The Power to Know
Postbus 3053
1270 EB Huizen
The Netherlands
http://www.sas.com/nl

Cosinus
Powerful and Reliable Programs for Statistics and Numerics
Grotestraat 401a, Waalwijk
Postbus 220
5150 AE Drunen
The Netherlands
http://www.cosinus.nl