Tags: Colloquium Series

The Statistics Department hosts weekly colloquia on a variety of statistcal subjects, bringing in speakers from around the world.


Dennis Lin

Dimensional Analysis (DA) is a fundamental method in the engineering and physical sciences for analytically reducing the number of experimental variables prior to the experimentation.  The principle use of dimensional analysis is to reduce from a study of the dimensions of the variables on the form of any possible relationship between those variables.  The method is of great generality.  In this talk, an overview/introduction of…


Hokwon Cho

We propose sequential methods for obtaining approximate confidence limits and optimal sample sizes for the risk ratio (RR) of two independent binomial variates and a measure of reduction (MOR). The procedure is developed based on a modified maximum likelihood estimator (MLE) for the ratio. First-order asymptotic expansions are obtained for large-sample properties of the proposed procedure and we investigate its finite sample behavior through…


Sujit Ghosh

Data processing and source identification using lower dimensional hidden structure plays an essential role in many fields of applications, including image processing, neural networks, genome studies, signal processing and other areas where large datasets are often encountered. Representations of higher dimensional random vector using a lower dimensional vector provide a statistical framework to the identification and separation of the sources.…


Bradley Jones

Latin Hypercube designs (LHD) are in standard use as plans for deterministic computer experiments. However, these designs depend on the ability of the investigator to set each factor independently of all the others. To be specific, the implied design region for an LHD is a square, cube or hypercube. However, there are cases where some parts of such a design region may be inaccessible or even nonsensical. In such cases it is useful to be able to…


Feifang Hu

Advances in genetics have allowed scientists to identify genes (biomarkers) that are linked with certain diseases. To translate these great scientific findings into real-world products (personalized medicine) for those who need them, clinical trials play an essential and important role. To develop personalized medicine, we need new designs of clinical trials so that genetics information and other biomarkers can be incorporated in treatment…


Bruce Craig

Immunohistochemical (IHC) staining is widely used in the diagnosis of cancer. Current methods for IHC scoring rely on a number of subjective evaluations.  A pathologist, for example, has to assess the overall level of staining of the tumor as negative, weak, intermediate, or strong, and then make a secondary subjective assessment of the percentage of cells that fall into each of these staining intensity categories.  Current inter- and…


Robert delMas

Preliminary results are presented from an ongoing study of the development of tertiary students’ reasoning in a one-semester college-level statistics course. The modeling and simulation-based course relies on randomization and bootstrap methods for inference. Students in the statistics course learn to use TinkerPlots® to create "just by chance" models that form the basis of simulated distributions of sample statistics in order to draw an…


Adrijo Chakraborty

In model-based survey sampling Hierarchical Bayesian (HB) methods have gained immense popularity. One of the major reasons for this popularity remains the convenience in implementation of HB models using MCMC methods even when the models are complex. An inevitable part of this approach is elicitation of the priors for the parameters involved in the model. Authentic expert information can be incorporated by assigning suitable subjective prior…


Pritam Ranjan

Space-filling designs are widely used for emulating computer simulators. Over the last three decades, a wide spectrum of Latin hypercube designs (LHDs) has been proposed with different space-filling criteria like minimum correlation among factors, maximin inter-point distance, and orthogonality among the factors. In this talk I will present a new class of space-filling designs. These designs are derived from randomization defining contrast…


Nilanjan Chatterjee

Large genome-wide association studies are now consistently pointing towards an extremely polygenic model for complex diseases. Such models may involve thousands of susceptibility markers, each conferring only a modest risk, but collectively they could be explaining substantial variation in disease-risks in populations. Further, a few large studies of gene-environment interactions indicate that genetic and environmental risk-factors may broadly…
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