Mu Sigma Rho 2011 Inductees

The Department wishes to congratulate its second class of Mu Sigma Rho inductees. The following students will be inducted at 2:30 on April 29th:

Undergraduate Level Inductees:
John Averick, Jessica Floyd, Alexander Lyford, Stephen Morris, Julia Orr, Jamaal Parker, Zachary Robbins, Neeraj Sriram, Christopher Tenza, Nathan Ulrich

Graduate Level Inductees:
Ashley Askew, Andy Bartlett, Huanyao Gao, Qianying Hong, Siyan Hu, Adam Jaeger, Leopold Matamba, David Nelson, Chris O'Neal, Eugine Song, Junqi Yin, Guannan Wang, Xuedong Wu

Fri, 04/29/2011
Alumni News: 

Adam Jaeger earns Honorable Mention from NSF

Adam Jaeger has earned an Honorable Mention for his recent proposal submitted to the NSF's Graduate Research Fellowship Program. From the Program Solicitation, "The NSF accords Honorable Mention to meritorious applicants who do not receive fellowship awards. This is considered a significant national academic achievement." Adam is in his second year of the graduate program, will earn his MS degree in Statistics in May, and will continue on in the PhD program with TN Sriram as his research advisor. Great job, Adam!

Wed, 04/06/2011
Alumni News: 

Undergraduate Student, Julia Orr, elected to Phi Beta Kappa

The Department wishes to congratulate statistics undergraduate student, Julia Orr, on being elected to Phi Beta Kappa, the nation’s oldest and most widely-known academic honorary society. An invitation for induction to Phi Beta Kappa is only offered to the most outstanding arts and sciences students, of which Julia is well deserving. Great job, Julia!

Fri, 03/18/2011
Alumni News: 

Robust Event-Related FMRI Designs Under A Nonlinear Model

Previous studies on event-related functional magnetic resonance imaging (ER-fMRI) experimental designs are primarily based on linear models, in which a known shape of the hemodynamic response function (HRF) is assumed. However, the HRF shape is usually uncertain at the design stage. To address this issue, we consider a nonlinear model to accommodate a wide spectrum of feasible HRF shapes, and propose an approach for obtaining maximin effcient designs. Our approach involves a reduction in the parameter space and an ecient search algorithm.

TR Number: 
Ming-Hung Kao, Dibyen Majumdar, Abhyuday Mandal, and John Stufken
Key Words: 
A-optimality; Genetic algorithms; Hemodynamic response function; Information matrix; Maximin effcient designs

To request a copy of this report send an email to Julie Davis with the technical report number and a pdf copy, if available, will be sent to you.


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