**Statistics Discussion Group**

Parker Hall 362

Mondays, 2 - 4 pm

Each time, a speaker will discuss something selected by the speaker. It is a good opportunity if you are interested in research in Statistics. You can check the full schedule by clicking here

Everyone is welcome.

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**Monday, April 8, 2013**

**Dr. Peng Zeng,** speaker

Title: Degrees of freedom in linear regression

Abstract: In this talk, we will review the existing results on degrees of freedom and discuss its application in linear regression.

**Monday, April 1, 2013**

**Dr Ash Abebe,** speaker

Title: On nonlinear signed-rank estimation

Abstract: I will discuss robust signed-rank estimation of the parameters of a general nonlinear regression model. Robustness is achieved by down-weighting in gradient space. I will briefly discuss extensions to harmonic type models used in texture modeling and signal processing.

This is based on joint work with current student Brice Merlin and former student Huybrechts Bindele.

March 25, 2013

**Dr Guanqun Cao** will discuss

Guo, Zhou, Huang, and Hardle (2013). Functional data analysis of generalized quantile regression

PDF version of the lecture notes is available at

http://sfb649.wiwi.hu-berlin.de/papers/pdf/SFB649DP2013-001.pdf

**March 18, 2013**

**Dr Xiaoyu Li** will continue to discuss Graphical models.

A. Montanari (2011). Lecture Notes for Inference in Graphical Models.

Pdf version is available at http://www.auburn.edu/%7ezengpen/seminar/Graphical-Models.pdf

**March 11, 2013**

**SPRING BREAK**

February 25, 2013

**Dr Guanqun Cao** will discuss the following paper.

I. Epifanio and N. Ventura-Campos (2011). Functional data analysis in shape analysis. Computational Statistics and Data Analysis, Vol 55, pp. 2758--2773.

Abstract: Suppose that k treatments under comparison are ordered in a certain way. For example, the treatments may be increasing dose levels in dose response experiments. The exponential distribution is generally used to model the effective duration of a drug, where the location parameter is referred to as the latency period that may decrease/increase with increase in dose. I will discuss exact tests for detecting such patterns. I will present a simple recursive integration method that can be used for computing the critical constants. This recursive method is a variation of the ones described in the following two papers by A. J. Hayter:

Recursive integration methodologies with statistical applications. J. Statist. Plann. Inference 136 (2006), 7, 2284 -2296.

Recursive integration methodologies with applications to the evaluation of multivariate normal probabilities. J. Stat. Theory Pract. 5 (2011), 4, 563-589.

**February 11, 2013**

**Dr Nedret Billor** will talk about an ongoing research in collaboration with Seokho and Hyejin.

Title: M-type Smoothing Spline Estimators for Principal Functions

Abstract: We propose a robust method for estimating principal functions based on MM estimation. Specifically, we formulate functional principal component analysis into alternating penalized M-regression with a bounded loss function. The resulting principal functions are given as M-type smoothing spline estimators. Using the properties of a natural cubic spline, we develop a fast computation algorithm even for long and dense functional data. The proposed method is efficient in that the maximal information from whole observed curve is retained since it partly downweighs abnormally observed individual measurements in a single curve rather than removing or downweighing a whole curve. We demonstrate the performance of the proposed method on simulated and lip movement data and compare it with the conventional functional principal component analysis and other robust functional principal component analysis techniques.

**February 04, 2013**

**Dr. Peng Zeng ** will discuss

Li, Chun, and Zhao (2012). Sparse estimation of conditional graphical models with application to gene networks. Journal of the American Statistical Association, Vol 107, pp. 152--167.

A PDF version of the paper is available at the following link (from an on-campus IP address) http://www.tandfonline.com/doi/pdf/10.1080/01621459.2011.644498

**January 28, 2013**

**Speaker: Dr Xiaoyu Li** will discuss

A. Montanari (2011). Lecture Notes for Inference in Graphical Models.

You can find the pdf version of the lecture notes by clicking here