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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.

A vast majority of the published cancer studies in the past few decades was conducted on cancer cells rather than cancer tissues. Knowing that the microenvironment plays key roles in cancer initiation, development and metastasis, we must reassess the true relevance of many of these published results to cancer. We have recently developed a new framework for cancer studies by treating cancer as a survival process under increasingly more…
In this talk the three-factor Fama-French regression model (1992~1995) is introduced, where the three factors are the market risk premium (MRP), small-minus-big risk premium (SMB) and high-minus-low risk premium (HML).  It is known that the factors MRP, SMB and HML can affect a stock portfolio’s return.  According to the Fama-French regression model, their six types of stock portfolios created by company size (Small or Big) and its…
Abstract: Wavelet shrinkage methods that use complex-valued wavelets provide additional insights to shrinkage process compared to standardly used real-valued wavelets. Typically, a location-type statistical model with an additive noise is posed on the observed wavelet coefficients and the true signal/image part is estimated as the location parameter. Under such approach the wavelet shrinkage becomes equivalent to a location estimation in the…
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…

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