Tags: Colloquium Series

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


Ashley Askew

Empirical likelihood is a nonparametric method based on a data-driven likelihood. The flexibility of empirical likelihood facilitates its use in complex settings, which can in turn create computational challenges. Additionally, the Empty Set Problem (ESP) which arises with the Empirical Estimating Equations approach can pose problems with estimation, as data are unable to meet constraints when the true parameter is outside the convex hull. As an…


Donald Richards

We consider problems in statistical inference with two-step, monotone incomplete data drawn from a multivariate normal population. We derive stochastic representations for the distributions of the maximum likelihood estimators of the population mean vector and covariance matrix and obtain results for inference on the mean vector and covariance matrix, including: lower bounds on the level of confidence associated with ellipsoidal confidence…


Yuan Xue

Sufficient dimension folding is the technology to reduce the dimensions of matrix- or array-valued objects as well as keep their data structure.  In this talk, I consider the sufficient dimension folding for the regression mean function when predictors are matrix- or array-valued. I propose the concept of central mean folding subspace and its two local estimation methods: folded outer product of gradients estimation (folded-OPG) and folded…


Wenxuan Zhong

Recently, a low cost yet highly sensitive colorimetric sensor array (CSA) for the detection and identification of volatile chemical toxicants has been developed. Classification analysis holds the key to the success of the array in discriminating multiple toxicants. The data output by the CSA are in the form of matrices, which render many traditional classification methods inapplicable. In this talk, I will introduce a matrix discriminant…


Ping Ma

At a depth of 2890 km, the core-mantle boundary (CMB) separates turbulent flow of liquid metals in the outer core from slowly convecting, highly viscous mantle silicates. The CMB marks the most dramatic change in dynamic processes and material properties in our planet, and accurate images of the structure at or near the CMB--over large areas--are crucially important for our understanding of present day geodynamical processes and the thermo-…


Brian Reich

Extreme environmental phenomena such as major precipitation events manifestly exhibit spatial dependence. Max-stable processes are a class of asymptotically-justified models that are capable of representing spatial dependence among extreme values. While these models satisfy modeling requirements, they are limited in their utility because their corresponding joint likelihoods are unknown for more than a trivial number of spatial locations,…


Donald Richards

We analyze the mathematical foundations of three types of structured financial products: return optimization securities, yield magnet notes, and reverse exchangeable notes. These products were sold widely to retail "investors" in the mid-2000s. On the basis of their mathematical structure, we infer that these products could provide positive returns to a purchaser only if the stock market had continued on an enormous upward climb for most or all…


Ling Lan

We propose nonparametric estimators for the state occupation probabilities in a given state adjusting for the informative cluster size and one covariate at a time in a multistate model. This is a non-trivial problem since the state occupied is determined at a single inspection time for each subject and a group of subjects belongs to a cluster where cluster size is informative to their state status. Nonparametric weighted monotonic regression and…


Eric Chicken

Many modern processes are capable of generating rich and complex data records not readily analyzed by traditional techniques. A single observation from a process might consist of n pairs of bivariate data that can be described via some functional relation (for example, a sequence of radar reflection signals measured over time). Or, each observation in a process may be a sample of data from some distribution. Methods are proposed here for…


Eric Feigelson

This talk provides an introduction to challenging statistical problems arising in the study of celestial objects: planets, stars, galaxies and the Universe as a whole. We start with a review of the close historical links between astronomy and statistics, from the ancient Greeks through Laplace and Gauss. However, the communities diverged during the 20th century, developing into a poor state with great needs for advanced methodology but weak…
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