Department of
Mathematical Sciences University of
Nevada, Las Vegas
20102011 [20062008] [20082009] [20092010]
[20112012] [Current
Year] For more information, contact the Colloquium/Seminar
Coordinator, Dr. Hokwon Cho (To see Math Dept Colloquia/Seminars, click next: Math Dept Seminar) 
Fall 2010 
[Abstract] Mapping of small
area mortality risks is a widely used technique in public health and in other
area of statistical applications. The commonly used measure of risk, the
standardized mortality ratio is not reliable due to its high variability in
areas with low population. Advanced
statistical techniques, such as, hierarchical modeling is common to overcome
this issue. However the spatially correlated structures often possess
challenges for their implementation and inferences. In this talk we will
discuss the statistical issues from frequentist and
Bayesian perspective and will offer some new ways of solving the problem.
Amgen Inc. [Abstract] In clinical trials
it is quite common to test more than one dose for efficacy against placebo or
an active control arm. Regulatory agencies such as Food and Drug administration
insist that if there are multiple comparisons to be made in a clinical trial
then familywise error rate should be controlled—typically at 5% level. A closed testing procedure was developed
by Marcus, Peritz and Gabriel and has been the
mathematical foundation for multiple testing procedures. In general, we need
to consider all possible intersections of the null hypotheses of interest.
A hypothesis is rejected if its associated test and all tests
associated with hypotheses implying it are significant. We shall explore
implications of this procedure to generate interesting tests that control
familywise error rate at a given level.
University of Nevada, Las Vegas [Abstract]
We
present a sequential method for obtaining approximate confidence limits for
the ratio of two independent binomial proportions based on a slightly
modified maximum likelihood estimator. Largesample properties of the
proposed sequential estimator are studied. 
Spring
2011 
[Abstract] Medical research is often interested in
finding subgroups in an outlier group. For example, a certain medical
condition can be more frequent in a small group that is different from the
majority of population. One approach to find groups in a data set is using
cluster analysis. Cluster analysis has been widely used tool in exploring
potential group structure in complex data and has received greater attention
in recent years due to data mining and high dimensional data such as
microarrays. In this presentation, I will introduce splitandrecombine
procedure and its application for a medical data set. In addition,
analysis results of the same data using other clustering methods will be
discussed.
[Abstract] One comes across directions as the
observations in a number of situations. The first inferential question that one
should answer when dealing with such data is, “Are they isotropic or
uniformly distributed?” The answer to this question goes back in history
which we shall retrace a bit and provide an exact and approximate solution to
this socalled “Pearson’s Random Walk” problem.
[Abstract] In this talk, parametric fractional
imputation is proposed as a frequentist approach of
generating imputed values. Using the fractional weights, the Estep of the EM
algorithm can be approximated by the weighted mean of the imputed data
likelihood where the fractional weights are computed from the current value
of the parameter estimates. Some
computational advantage over the existing methods can be achieved using the
idea of importance sampling in the
[Abstract] This talk will introduce a flexible class of
models for relational data based on a hierarchical extension of the
twoparameter PoissonDirichlet process. The models are motivated by two
different applications: 1) A study of cancer mortality rates in the 
