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Slideshow

Tags: Colloquium Series

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

Gene duplication is the key mechanism for evolutionary change. To infer the timing and nature of gene duplication, the 'data' used are the end result of various pipelines. In this talk, I will summarize how the 'data' are obtained, explore the shortcomings of analyses in the literature, and end with current work on overcoming these shortcomings. The interesting statistical problems are that the 'data' are maximum likelihood estimates, and that…
Dr. Wu will speak at this year's Bradley Lecture on Friday April 25, 2014 at 4:30pm.  An RSVP is required to attend this lecture. Young (and some not-so-young) researchers often wonder how to extract good research ideas and develop useful methodologies from solving real world problems. The path is rarely straightforward and its success depends on the circumstances, tenacity and luck. I will use three examples to illustrate how I trod the…
One situation that arises in the field of functional data analysis is the use of imaging data or other very high dimensional data as predictors in regression models.  A motivating example involves using baseline images of a patient's brain to predict the patient's clinical outcome.  Interest lies both in making such patient-specific predictions and in understanding the relationship between the imaging data and the outcome. …
The Dipsea is a 100 year old 8 mile running event that starts in Mill Valley CA and ends at the Pacific Ocean near Stinson Beach. What makes the event unique is its handicap system. Each age group for men and women receive a handicap time. For example, the slowest group, the AAA group, comprised of men 74 years old and older, boys 6 and under, women 66 and older, and girls 7 and under, receive a 25 minute handicap. But what makes the event…
This event has been canceled due to inclement weather.  Please stay tuned for future updates.       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…
Dr. Chaloner will speak at this year's UGA/Clemson Joint Seminar on Thursday April 17, 2014 at 3:45pm.  An RSVP is required to attend this lecture. Bayesian methods for statistical analyses require a different interpretation of probability than traditional “frequentist” methods.  The use of Bayesian methods is increasingly common and its flexibility has facilitated a wide range of scientific advances, especially in medicine. The first…
The analysis of functional neuroimaging data often involves the simultaneous testing for activation at thousands of voxels, leading to a massive multiple testing problem. This is true whether the data analyzed are time courses observed at each voxel or a collection of summary statistics such as statistical parametric maps (SPMs). It is known that classical multiplicity corrections become strongly conservative in the presence of a massive number…
This dissertation consists of two parts for the topic of sample integrity in high dimensional data. The first part focuses on batch eff ect in gene expression data. Batch bias has been found in many microarray studies that involve multiple batches of samples. Currently available methods for batch eff ect removal are mainly based on gene-by-gene analysis. There has been relatively little development on multivariate approaches to batch adjustment…
LISA and its partners will educate and train statisticians from developing countries to communicate and collaborate with non-statisticians and then support these statisticians to create statistical collaboration laboratories in their home countries to help researchers, government officials, local industries, and NGOs apply statistical thinking and data science to make better decisions through data. At LISA and elsewhere, we will unlock the…
Personalized information filtering extracts the information specifically relevant to a user, based on the opinions of users who think alike or the content of the items that a specific user prefers.  In this talk, we discuss latent models to utilize additional user-specific and content-specific predictors, for personalized prediction.  In particular, we factorize a user-over-item preference matrix into a product…

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