## Scientific General Events

Waves, Vortices, and Climate Modelling

Welcome to the 2008 Applied Mathematics Graduate Student Conference (AMGSC) webpage. The conference was held on Saturday, January 26 and Sunday, January 27 at Simon Fraser University. Some students gave short presentations based on past course project or current research.

**Speaker**: Derek Bingham

**Title**: Statistical Research in a Collaborative Environment

Modern statistical research is often motivated by applied problems that arise in other areas of science. Finding solutions to these applied problems leads to collaborations between statisticians and subject-specific researchers. Working in such a collaborative environment brings much benefit to both parties, but is not without challenges. This talk will relate some of my experiences working in such an environment, and how one might build successful long-term collaborative relationships.**Title**: Confidence intervals for proportions and quantiles with application to NHANES

**Speaker**: Cindy Feng

It has been noted that the usual confidence interval for proportions does not perform well for large and small values of p. In surveys the issue is complicated by the survey design and issues of whether to use design effects, effective sample size and effective degrees of freedom arise. The question is which of the many possible confidence intervals available should be recommended for the U.S. National Health and Nutrition Examination Surveys (NHANES) end users and what cautions should be given. In addition, the issues may be different if the interval is actually being used in combination with Woodruff’s method to form confidence intervals for small and large quantiles.**Title**: Median Loss Analysis

**Speaker**: Pen Yu

In classical decision theory in statistics, Wald (1950) first introduced the risk function, and used it to evaluate how good the estimators are. Conventionally, the risk is assumed to be finite in most situations. In other words, we cannot handle the problems of heavy-tail distributions like the Cauchy distribution. In this talk, I will introduce the median version of the risk, called the median loss, and compare it with the risk and other domination criteria. Moreover, we will see that the estimator by the median loss approach is more loss robustness than the estimator by the risk, such as the Bayes estimator.**Title**: Statistical Monitoring of Clinical Trials with Multivariate Response or Multiple Arms Using Repeated Confidence Bands

**Speaker**: Lihui Zhao

**Coauthors**:

X. Joan Hu (Simon Fraser University) Stephen W. Lagakos (Harvard University)

Clinical trials with multivariate response or multiple arms have become increasingly common because of their potential efficiency and cost saving. Interim analyses of such studies are often guided by parametric assumptions for the underlying probability models. There are situations where it is not clear at the outset how the responses differ among the treatment groups and what kinds of differences are clinically meaningful. More flexible designs and monitoring procedures are therefore desirable. In this talk, we extend the repeated confidence bands approach (Hu and Lagakos, 1999) to studies with multivariate target function. We use a recent AIDS clinical trial to illustrate how to apply the multivariate repeated confidence bands (MRCB) approach in practice.**Title**: Prior Sensitivity and Cross-Validation using Sequential Monte Carlo

**Speaker**: Luke Bornn

In a Bayesian setting, adequately approximating the model of interest can be computationally expensive in the order of hours or even days. Prior sensitivity and cross-validation are both tasks that involve repeating this approximation repeatedly, potentially hundreds or thousands of times. In this talk I will demonstrate how sequential Monte Carlo methods can make prior sensitivity and cross-validation feasible in situations where the distribution of interest is not available analytically, reducing computational time by an order of magnitude or more in most settings.**Title**: The Publication Process in Statistics

**Speaker**: Paul Gustafson

Peer-reviewed academic journals are central to scientific life. Scientists of all stripes spend substantial proportions of their time reading, writing, and reviewing for journals. Based on my experiences as an author, a reviewer, an associate editor, and an editor, I will make some comments on how academic journals function, and try to offer some advice on navigating the publication process.**Title**: Finding approximate solutions to combinatorial problems with very large datasets using BIRCH

**Speaker**: Justin Harrington

Over time the boundaries between Computer Science and Statistics have blurred, with a number of disciplines (e.g. Machine Learning) being actively researched in both schools. One such technique is called BIRCH (Balanced Iterative Reducing and Clustering using Hierarchies) (Zhang et al, 1997), which is a data pre-processing tool used for clustering extremely large datasets with a k-means algorithm. The advantage of this algorithm is that it generates "sufficient statistics" with only one pass of the dataset, and these values can then be used instead of the whole dataset for certain applications.

In this talk we demonstrate this algorithm's application in two fields, namely robust statistics and (if time permits) a new clustering method called Linear Grouping Analysis (Van Aeslt et al, 2006).**Title**: Designs for Computer Experiments

**Speaker**: Chunfang Lin

Latin hypercube designs have been widely adopted in conducting computer experiments. In this talk, we introduce methods for constructing a rich class of Latin hypercube designs with appealing projection and space-filling properties. The class includes many orthogonal Latin hypercube designs that are not available in the literature, as well as nearly-orthogonal Latin hypercubes and two-level orthogonal-array based orthogonal Latin hypercube designs. This is joint work with Randy R. Sitter.The

**29th Annual Alberta Statisticians Meeting**is sponsored by the Department of Mathematics and

Statistics and the Faculty of Science at the University of Calgary, and also by PIMS.This meeting serves many purposes. It allows faculty and graduate students working in probability and statistics

at different universities in Alberta to interact, make contacts, and discuss their research. It serves as a training

vehicle for highly qualified people (HQP) working in probability and statistics. It affords statisticians working in

the private and non-academic public sector to discuss their problems with academic researchers. In addition,

it affords graduate students an opportunity to present their work and themselves to possible future employers.**Registration will be at the door.**For further information, please contact David Scollnik at scollnik@math.ucalgary.ca.

The Cycle Double Cover Conjecture (CDC) was proposed independently by

P.D. Seymour (1979) and G. Szekeres (1973). The conjecture is easy to state:

"For finite every 2-connected graph, there is a list of cycles (polygons)

such that every edge of the graph is an edge of exactly two cycles

in the list."As an example, if the graph is embedded in a surface (without crossing

edges) in such a way that all faces are bounded by cycles,

then the boundary cycles of the faces will "double cover" the edges.

Although the statement of the conjecture is very simple, the solution

has eluded dozens of attacks over 30 years.This conjecture (and its numerous variants) is considered by most graph

theorists to be one of the major open questions in the field.

One reason for this is the close connections that this problem has

with topological graph theory, the theory of Nowhere-zero flows,

graph colouring and polyhedral combinatorics. MathSciNet lists more

25 articles with "cycle double cover" (or "double cycle cover") in

the title.The workshop will include some formal presentations

with the purpose of bringing the participants up to date on

techniques and recent results. Long collaborative working periods will

take the majority of the working time.The 19th Annual Canadian Conference on Computational Geometry (CCCG 2007) will

be held in Ottawa, Canada on August 20-22, 2007 at Carleton University, with a

welcome reception on the evening of August 19th.CCCG focuses on the computational aspects of geometric problems. Computational

Geometry applies to all fields that touch geometric computing. Application

areas are as diverse as computer graphics and animation, computer vision,

CAD/CAM, GIS, pattern recognition, wireless communication, robotics, urban

planning, graph drawing, or statistical analysis to name just a few.CCCG is intended to be a forum, accessible to a broad variety of researchers in

the area, to disseminate and discuss new results. All submitted papers will be

refereed, but we have no maximum target on the number of submissions that are

accepted. All papers that present new, original, and error free results that

are of interest to the greater computational geometry community will be

accepted. The intended audience for this conference includes graduate and

undergraduate students, researchers in the area and members of industry that

work in areas requiring the use of intensive geometric computation.The International Conference of Theoretical and Numerical Fluid Mechanics

III is being held in honor of Professors Giovanni Paolo Galdi and Rolf

Rannacher, in celebration of their sixtieth birthdays. Reflecting their

interests, it will be an interdisciplinary meeting within the general field

of mathematical and computational fluid dynamics, devoted mainly to

Newtonian and non-Newtonian viscous flow. While promoting a high quality of

mathematical treatment, no area of practical application will be excluded

due to the present intractability of interesting mathematical difficulties.

Thus, there will be lectures on turbulence, blood flow, sedimentation,

fluid structure interaction, flow control, and the dynamical systems

perspective, as well as key issues of the Navier-Stokes theory.Short courses will be offered by Professors Galdi and Rannacher on the two

days preceding the conference. Professor Rannacher will lecture on

“Numerical methods for the simulation of fluid-structure interaction”.

Professor Galdi will lecture on “Topics in the Mathematical Theory of

Fluid-Solid Interaction”.Registration is open to the general scientific and engineering community.

All registrants are invited to give poster presentations. Also, all

registrants along with their families are welcome and encouraged to join in

all of our sponsored social events.**PIMS has provided special funds for**.

supporting the travel of graduate students to attend this meeting. Graduate

students wishing such support should apply for it by writing to John

Heywood at heywood@math.ubc.caCECM, Maplesoft, MITACS, IRMACS and PIMS are pleased to present "CECM 2007", a summer conference hosted by CECM under the title "Summer Workshop on Computational Mathematics" at Simon Fraser University.

The Workshop Program includes talks and a poster session which cover diverse topics in mathematics with an emphasis on computation.

Registration is required.

For more information, please visit:

www.cecm.sfu.ca/events/CECM07/- For more information, please click here to visit the external site.
The climate statistics workshop provided a venue for scientific researchers and end users to discuss how statistical information can benefit agriculture, water and other climate sensitive operations. Applied scientific presentations increased understanding of what can be provided analytically using 'easy to understand statistics.' The usefulness and limitations of the tools were assessed by the user community, who engaged researchers in a dialogue aimed at suggesting appropriate statistical techniques for risk reduction. The dialogue was achieved by including users of climate information as workshop participants. Participants include representatives of government departments, commodity brokers, financial representatives and community groups whose activities are impacted by weather and climate.