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Subject:

Seminars: updated Cambridge list

From:

Susan Pitts <[log in to unmask]>

Reply-To:

Susan Pitts <[log in to unmask]>

Date:

Fri, 29 Oct 1999 15:15:14 +0000 (GMT)

Content-Type:

text/plain

Parts/Attachments:

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text/plain (208 lines)

Please note that updated Statistical Laboratory seminar lists are shown
on our web page at

            http://www.statslab.cam.ac.uk/Dept/statsemmich1999.html


                             SEMINARS
                   ROOM 27, STATISTICAL LABORATORY
                      UNIVERSITY OF CAMBRIDGE

                   ********************************
                   *  ALL INTERESTED ARE WELCOME  *
                   ********************************



                   *******************************
                        Friday 5  November  1999
                   *******************************


2.00 John Wood, SmithKline Beecham Pharmaceuticals

THE ANALYSIS OF EMBEDDED DATA IN QUANTITATIVE STRUCTURE-ACTIVITY
RELATIONSHIPS
(QSAR)

QSAR is the attempt to relate the biological activity of molecules to
their chemical structure in a quantitative fashion. This quite often leads
to the problem of discriminating between two classes (the biologically
active class, and the inactive class) where the former is 'embedded' in
the latter with respect to their chemical properties. Traditional methods
of discrimination based on differences between means are no good here, and
the talk describes some more recent algorithms that have been developed
with this problem specifically in mind.


Graeme Archer, SmithKline Beecham Pharmaceuticals

STATISTICAL THINKING AND HIGH THROUGHPUT TOXICOLOGICAL SCREENING

(Joint work with Sophie Wildsmith, Molecular and Immunological
Toxicology, Safety Assessment, Smithkline Beecham).

The Genomic and Proteomic Screening group in Molecular and Immunologic
Toxicology, Safety Assessment, are developing a high throughput screen for
early detection of unsuitable toxicity in novel compounds.

The aim is to develop a microgrid array of genetic material, expose the
genes to tissue (or ultimately, cells) treated with the compound, and
categorise the compound into a particular class of toxicity on the basis
of the observed pattern of genetic expression on the grid.

This talk outlines the role of statistical thinking in the development of
the process. Design of Experiments was used extensively to optimise the
experimental process and determine of components of variance.  We have
developed a simple bootstrap test procedure for assessing the significance
and degree of up or down regulation of the genetic material.  Problems
with the standardisation of grid results are being assessed through a
variety of methods, which we discuss. Finally, some early classification
results are presented, using nothing (so far) more complicated than
principal components and logistic regression.


                          

                   *******************************
                        Friday 12 November  1999
                   *******************************



2.00 Andy Burbanks, Cambridge Univeristy

SOME NATURAL INDEPENDENCE PHENOMENA

Part of Hilbert's famous Programme was the intention to find a
self-contained formal foundation for mathematics. However, Godel's theorem
demonstrates that sufficiently powerful formal systems will always be
incomplete. The undecidable statements constructed in Godel's proof may
seem rather artificial and contrived; does Godel's theorem actually matter
to ``everyday'' mathematics?

This talk will give some examples of ``natural independence phenomena''
(more natural-looking undecidable statements), showing along the way that
Hercules can defeat the many-headed Hydra. My interest in this area is
mainly recreational; I have always been fascinated by certain aspects of
logic and would like to help make these results accessible to a wider
audience.

The talk does not assume any special previous knowledge.



                        

                     *******************************
                         Friday 19 November 1999
                     *******************************




2.00 Frank Ball, Nottingham

STATISTICAL INFERENCE FOR SIR EPIDEMICS AMONG A POPULATION OF
HOUSEHOLDS

This talk is concerned with a stochastic model for the spread of an SIR
(susceptible -> infected -> removed) epidemic among a population
consisting of a large number of small households, with different rates for
between-household and within-household infections.  The threshold
behaviour of the model is briefly outlined.  Methods for making
statistical inferences about the parameters governing such epidemics from
final outcome data are described and their asymptotic properties, as the
number of households becomes large, are determined.  The theory is
illustrated by simulations and by an application to data on influenza
epidemics in Tecumseh, Michigan.



                       

                  *******************************
                     Friday 26 November 1999
                  *******************************




2.00 J. Bertoin, Paris VI

A SYSTEM OF STICKY PARTICLES AND THE ADDITIVE COALESCENT

We establish a connection between two different models of clustering: the
deterministic model of sticky particles which describes the evolution of a
system of infinitesimal particles governed by the dynamic of completely
inelastic shocks (i.e. clustering occurs upon collision with conservation
of masses and momenta), and the random model of the so-called additive
coalescent in which velocities and distances between clusters are not
taken into account.  The connection is obtained when at the initial time,
the particles are uniformly distributed on a line and their velocities are
given by a Brownian motion.






                      

                     *******************************
                        Friday 3 December 1999
                     *******************************


2.00 Song Chen, La Trobe University

CONFIDENCE INTERVALS BASED ON A LOCAL LINEAR SMOOTHER

Point-wise confidence intervals for a nonparametric regression function in
conjunction with the popular local linear smoother are considered. The
confidence intervals are based on the asymptotic normal distribution of
the local linear smoother. Their coverage accuracy is evaluated by
developing Edgeworth expansion for the coverage probability.

We find two surprising results. One is that the coverage error near the
boundary of the support of the regression function is of a larger order
than that in the interior, which implies that the local linear smoother is
not adaptive to the boundary in term of coverage. This is quite unexpected
as the local linear smoother is adaptive to the boundary in term of bias
and variance.  The other is that confidence intervals based on the
Nadaraya-Watson estimator achieve the same order of coverage error as that
based on the local linear smoother, but are shorter near the boundary.

The empirical likelihood provides a remedy to the boundary problem of the
asymptotic local linear confidence interval as it chooses its own variance
estimator "naturally", different from the standard asymptotic variance.


3.30 Ron Doney, Manchester

SOME ASYMPTOTIC RESULTS FOR RANDOM WALKS AND LEVY PROCESSES



Seminar organizer: Susan Pitts

Please see also the /~grg/seminars/probsem.html -  Informal Probability
Seminars.



UNIVERSITY OF CAMBRIDGE
DEPARTMENT OF PURE MATHEMATICS AND MATHEMATICAL STATISTICS
STATISTICAL LABORATORY
16 MILL LANE, CAMBRIDGE CB2 1SB
Tel: (01223) 337958
Fax: (01223) 337956







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