Tags: Colloquium Series

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


Yi Li

We propose a new class of estimating equation-based Dantzig selectors that can achieve simultaneous estimation and variable selection in the absence of a likelihood function, even when the number of covariates exceeds the number of samples. Our research was motivated by practical problems encountered in two studies: a clinical trial of therapies for head and neck cancer, and a genomics study of multiple myeloma patients. These problems proved…


Xiaobo Ding

We propose a constrained least square estimator of the transformation function of a partially linear single-index transformation model, where the transformation function, single-index function and error distribution are all nonparametric. The estimators of the regression coefficients and the single-index function are provided by the similar idea to the minimum average variance estimation method. Basis function approximation is employed to…


Warren Kuhfeld

Marketing, transportation, environmental, and other researchers need to understand how people make choices. Researchers design experiments, collect data, and fit models to understand people’s preferences. This talk will explain some commonly used methods for designing choice experiments along with a series of SAS tools that you can use to design and evaluating choice experiments. Design methods include generic and alternative-specific choice…


Haiyan Cai

I will talk briefly some of my recent research on random networks. In the first part of the talk, we will focus on the connectivity of a random network. The network is formed from a set of randomly located points and their connections depend on the distance between the points. It is clear that the probability of connection depends on the density of the points. We will explore some properties of this probability as a function of the point density…


Mi-Ok Kim

We consider a random effects quantile regression analysis of clustered data and propose a semiparametric approach using empirical likelihood. The random regression coefficients are assumed independent with a common mean, following parametrically specified distributions. The common mean corresponds to the population-average effects of explanatory variables on the conditional quantile of interest, while the random coefficients represent cluster…


Lianming Wang

Interval-censored data naturally arise in many fields such as aids clinical trial studies and follow-up medical studies. The main feature is that the failure time of interest is not observed exactly but is known to fall within some interval. Regression analysis on interval-censored data is challenging due to the complex data likelihood and the censoring mechanism producing such data. In this talk, I will review the commonly used semiparametric…


Ana-Maria Staicu

We introduce a novel class of models for functional data exhibiting skewness or other shape characteristics that vary with spatial location. Such data are not envisaged by the current approaches to model functional data, due to the lack of Gaussian – like features. Our methodology allows modeling the pointwise quantiles, has interpretability advantages and is computationally feasible. Our methods were motivated by and are illustrated with a…


MoonJung Cho

In applied work with generalized variance function models for sample survey data, one generally seeks to develop and validate a model that is relatively parsimonious and that produces variance estimators that are approximately unbiased and relatively stable. This development and validation work often begins with regression of initial variance estimators (computed through standard design-based methods) on one or more candidate explanatory…


William A. Brenneman

Modern industry is constantly seeking to efficiently produce new and improved products. Statisticians play a central role in helping the product team quickly identify areas for improvement and optimization. Many of the problems faced in industry can be solved with known statistical methods, while occasionally there are problems encountered that require original research. For a research statistician practicing in industry, these types of problems…


Somnath Datta

We will consider inference for various marginal temporal functions of a multistate system such as the state occupation probabilities, the integrated transition hazards, the state entry, exit and sojourn time distributions. For most parts, we will not assume a Markov or semi-Markov system. Nonparametric estimators under right censored, current status and interval censored data will be constructed. In this talk, we will consider construction of…
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