Tags: Colloquium Series

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


Pengsheng Ji

Consider a linear model Y = X + z, z  N(0; In). Here, X = Xn;p, where both p and n are large, but p > n. We model the rows of X as i.i.d. samples from N(0; 1 n ), where is a pp correlation matrix, which is unknown to us but is presumably sparse. The vector is also unknown but has relatively few nonzero coordinates, and we are interested in identifying these nonzeros. We propose the Univariate Penalization Screeing (UPS) for variable…


Kehui Chen

In this talk, I will first present a method for conditional distribution and quantile estimation when predictors take values in a functional space, which is an extension of the usual functional mean regression. The study is motivated and illustrated by an application to the assessment of children’s growth patterns. The proposed method is supported by theory and is shown to perform well in simulations. An extension of the proposed conditional…


Vadim Zipunnikov

We introduce a flexible inferential framework for the longitudinal analysis of ultra high dimensional data. Typical examples of such data structures include, but are not limited to, observational studies that collect imaging data longitudinally on large cohorts of subjects. The approach decomposes the observed variability into three high dimensional components: a subject-specific random intercept that quantifies the cross-sectional variability,…


Roger Woodard

Statistics 311 at NCSU is a large introductory course that serves over 700 students per semester. In this talk I will present the results of a redesign that transformed this course in a hybrid format. This project converted two of the three hours of student contact to an online format. Students still come together one day a week to participate in discussions where an instructor teaches them the important ideas and concepts. During this time…


Luyan Dai

In oncology trials with time to event as primary endpoints, the trial duration is mainly driven by the number of events observed to ensure sufficient power to draw confirmatory conclusions. The trial planning determined by clinical staff and the deterministic techniques fails to account for the uncertainties and stochastic fluctuations in the recruitment process and event evolvement. In this project, we incorporate a Poisson-gamma recruitment…


Warren Kuhfeld

This presentation begins with a behind-the-scenes look at how research statistician developers at SAS interact with customers and the statistical community to decide on new functionality in SAS/STAT. The presentation then provides a high-level tour of new directions and features in the most recent releases of SAS/STAT (9.2, 9.22, and 9.3). These releases deliver new procedures and enhancements for modern statistical graphics, Bayesian analysis,…


Hanxiang Peng

In this talk, we present maximum empirical likelihood estimation in the case of constraint functions that may be discontinuous and/or depend on additional parameters. The key to our analysis is a uniform local asymptotic normality condition for the local empirical likelihood ratio. This condition holds under mild assumptions and allows for a study of maximum empirical likelihood estimation and empirical likelihood ratio testing similar to that…


Yan Daniel Zhao

We present research on clinical trials with a sensitive subpopulation of patients, that is, a subgroup that is more likely to benefit from the treatment than the overall population. Given a sensitive subgroup defined by a prespecified classifier, for example, a clinical marker or pharmacogenomic marker, the trial’s outcome is declared positive if the treatment effect is established in the overall population or in the subgroup. We provide a…


Jane-Ling Wang

In this talk, we explore the modeling of survival data in the presence of longitudinal covariates. In particular, we consider survival data that are subject to both left truncation and right censoring. It is well known that traditional approaches, such as the partial likelihood approach for the Cox proportional hazards model encounter difficulties when longitudinal covariates are involved in the modeling of the survival data. A joint likelihood…


Hyonho Chun

Current genomics research indicates that statistical analysis based on individual genes may incur loss of information on the biological process under study. Better results can be derived from the analysis based on groups of genes, or gene networks. An informative characterization of a gene network is by the global Markov property, which can be inferred by the Gaussian graphical models (GGMs). In this talk, I will present two recent network…
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