SMS scnews item created by Michael Stewart at Fri 21 Aug 2015 0848
Type: Seminar
Distribution: World
Expiry: 28 Aug 2015
Calendar1: 25 Aug 2015 1800-1930
CalLoc1: Carslaw 535A
Auth: michaels@14-200-1-56.static.tpgi.com.au (mste2887) in SMS-WASM

Stats Society NSW Monthly Talk: Mueller -- Interactive and data adaptive model selection with mplot

This month’s Stats Society talk on Tuesday next week features our own Samuel Mueller! 
It’s also being held here in Carslaw Seminar Room 535. Details are below.

Cheers,

Michael

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Date: Tuesday, 25 August 2015

Time:

6:00pm - 6.30pm: Refreshments

6:30pm - 7.30pm: Lecture

7:45pm - onward: Dinner

Venue:

Carslaw Seminar Room 535, Level 5, Carslaw Building, University of
Sydney.

Associate Professor Samuel Mueller
University of Sydney

Interactive and data adaptive model selection with mplot

This talk focuses on the computational aspects of selection criteria that
are based on either inclusion or exclusion frequencies. We have developed
the mplot R package which provides a collection of functions to aid
exploratory variable selection. The package contains fast routines to make
available modified versions of the simplified adaptive fence procedure
(Jiang et al., 2009, Annals of Statistics) as well as other graphical tools
such as variable inclusion plots and model selection curves (Mueller and
Welsh, 2010, International Statistical Review; Murray et al, 2013,
Statistics in Medicine). A browser based graphical user interface is
provided to facilitate interaction with the results. These variable
selection methods rely heavily on bootstrap resampling techniques. Fast
performance for standard linear models is achieved using the branch and
bound algorithm provided by the leaps package. The graphical model
selection methods in mplot visualise popular model selection criteria that
involve minimizing a penalized function of the data over a typically very
large set of models. The penalty in the criterion function is controlled by
a tuning parameter which determines the properties of the procedure. The
implemented methods in mplot allow us to better explore the stability of
model selection criteria through model selection curves and this is
demonstrated through case studies.

Joint work with Garth Tarr (ANU); AH Welsh (ANU)

Biography of Associate Professor Samuel Mueller

Samuel Mueller was born and educated in Switzerland and received his PhD in
Mathematics from the University of Bern in November 2002. He joined the
University of Sydney in 2008 as a Lecturer, was promoted to Senior Lecturer
in 2010 and to Associate Professor in 2015. Previous appointments include a
postdoc at the ANU (2003-2004) as well as academic positions at the
University of Bern (2004-06) and the University of Western Australia
(2006-2008). He served recently as the Postgraduate Director in the School
of Mathematics and Statistics (2012-2015) and is currently enjoying a
sabbatical with various trips overseas and interstate. Samuel is a member
of the Statistics Research Group. His specialties include Model Selection,
Applied Statistics, Robust Methods and Extreme Value Theory. His research
is mostly motivated by statistical problems that enable to learn more from
omics, neuroscience and other complex data.


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