Tags: Colloquium Series

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

Network analysis is becoming one of the most active research areas in statistics. Significant advances have been made recently on developing theories, methodologies and algorithms for analyzing networks. However, there has been little fundamental study on optimal estimation. In this talk, we establish optimal rate of convergence for graphon estimation. For the stochastic block model with $k$ clusters, we show that the optimal rate under the mean…
In design of experiments, optimal designs are designs that  can glean the maximal amount of information from a study.   Therefore, an optimal design can reduce the number of ex- perimental units needed and saving the cost of study.   However, the research  in designing optimal experiments has not kept up with the increasingly complicated structure of data and models; especially for correlated data and multi-covariate…
We consider D-optimal designs with ordered categorical responses and cumulative link models. In addition to theoretically characterizing locally D-optimal designs, we develop efficient algorithms for obtaining both approximate designs and exact designs. For ordinal data and general link functions, we obtain a simplified structure of the Fisher information matrix, and express its determinant as a homogeneous polynomial. For a predetermined set of…
Advancement in technology and computing power have led to the generation of data with enormous amount of variables when compared to the number of observations. These types of data, also known as high dimension, low sample size, are plagued with different challenges that either require modifications of existing traditional methods or development of new statistical methods. One of these challenges is the development of Sparse methods that use only…
The analysis of univariate and multivariate longitudinal data (U/MLD) with censored and missing response has inspired considerable interest in the statistical community recently. In the case of MLD, estimating the contemporaneous correlation coefficient is of particular interest to applied researchers. In this dissertation, mixed model methodologies are investigated to analyze U/MLD with censored and missing response while accounting for complex…
This talk will have two components. In the first part, I will give an overview of NSF, and its resources that are relevant to the statistical science. Some related programs that are beyond the Division of Mathematical Science, such as the Big Data program and the Computational and Data-enabled Science and Engineering program, will be reviewed. Some suggestions regarding how to apply to these programs may be provided. In the second part of this…
Structured covariance matrices characterized by a small number of parameters have been widely used and play an important role in parameter estimation and statistical inference. To assess the adequacy of a specified covariance structure, one often adopts the classical likelihood-ratio test when the dimension of the data (p) is smaller than the sample size (n). However, this assessment becomes quite challenging when p is bigger than n, since the…
In this talk, we introduce a robust testing procedure — the Lq-likelihood ratio test (LqLR).  We derive the asymptotic distribution of our test statistic and demonstrate its robustness properties both analytically and numerically. We further investigate the properties of its influence function and breakdown point.  We also propose a method for selecting the tuning parameter q, and demonstrate that, with the q selected using our…