[18838] in s-news-athena
[S] Courses sponsored by ASA Section on Stat Computing: 1999 JSM
daemon@ATHENA.MIT.EDU (Ranjan Maitra)
Tue Aug 3 18:33:59 1999
Date: Tue, 3 Aug 1999 18:25:59 -0400 (EDT)
From: Ranjan Maitra <maitra@math.umbc.edu>
To: S-news <s-news@wubios.wustl.edu>
Message-Id: <Pine.LNX.4.04.9908031812100.3625-100000@param.math.umbc.edu>
Mime-Version: 1.0
Content-Type: TEXT/PLAIN; charset=US-ASCII
Hi,
Thought this might be relevant to some in this newsgroup. For more information,
please check Continuing Education courses at
http://amstat.org/meetings/jsm/1999/index.html.
Ranjan Maitra
CE Liason
ASA Section on Statistical Computing
1. 908C- Regression Graphics: Ideas for Studying Regressions thru Graphics
by Dennis Cook. (Sunday August 8, 1999: 8am -- 5 pm)
Description of CE
This course is on a new graphical context for regression that requires few
scope-limited conditions. The context centers on a sufficient summary plot
that contains all the information on the response that is available from
the predictors. The methodology for finding sufficient summary plots and
developing models from them is quite general and can be used in many
regression problems. It will be illustrated with a computer program
that will be made available to the participants. Participants will come
away with a new view of regression, new tools, a new appreciation of
graphics, and the ability to carry out more comprehensive and compelling
analyses.
2. 920C- Stochastic Optimization and the Simultaneous Perturbation Algorithm
by James Spall (August 10, 1999: 1-5 pm)
Description of CE Course
This course will introduce statistical practitioners and researchers to some
of the broad issues in the field of stochastic optimization and discuss a
relatively new stochastic optimization approach (simultaneous perturbation
stochastic approximation SPSA) that has attracted considerable international
attention in a variety of problems. The essential features of SPSA are its
efficiency for multivariate problems and its relative ease of implementation
for practitioners (which follows, among other aspects, by avoiding the
objective function gradient vector needed in many other methods). Applications
in statistical parameter estimation, neural network training, experimental
design, and simulation-based optimization will be discussed. Some comparisons
with genetic algorithms, simulated annealing, and other approaches will be
included. Since SPSA is relatively easy to implement, it is expected that
the participants will be able to quickly put into practice many of the
ideas in the course.
3. 923C- Statistical Shape Analysis by Ian Dryden and Kanti Mardia
(August 11, 1999: 9am-5pm)
Description of CE Course
Statistical Shape Analysis involves methods for the geometrical study of
random objects where location, rotation and scale information can be
removed. The subject is a new and exciting area of statistics, offering
many fresh challenges. There have been many advances made in the past 10
years, and there are a huge variety of applications. The course lays the
foundations of the subject, discusses key ideas and the very latest
developments, offers practical guidance, and gives comparisons of techniques.
The course primarily concentrates on landmark data, where key points of
correspondence are located on each object. Careful consideration of the
similarity in variances requires methods appropriate for non-Euclidean
data analysis. In particular, multivariate statistical procedures cannot
be applied directly, but can be adapted in certain instances. Various
applications will be given throughout, including in biology, medicine,
image analysis, genetics and agriculture.
***************************************************************************
Ranjan Maitra, Department of Mathematics and Statistics,
University of Maryland, Baltimore County, Baltimore, MD 21250, USA.
***************************************************************************
\|/ satyamevajayate | tamasomaajyotirgamaya \|/
-*- | -*-
/|\ TRUTH SHALL PREVAIL | FROM DARKNESS TO LIGHT /|\
***************************************************************************
Ph: 410-455-2436 FAX: 410-455-1066 http://www.math.umbc.edu/~maitra
***************************************************************************
-----------------------------------------------------------------------
This message was distributed by s-news@wubios.wustl.edu. To unsubscribe
send e-mail to s-news-request@wubios.wustl.edu with the BODY of the
message: unsubscribe s-news
