Department of Mathematics & Statistics Calendar Week of September 10 ‹ 16, 2007 Monday, September 10, 2007 1:30 PM MATH 126 Instructors Meeting 459 MSc 3:30 PM Algebra Seminar 459 MSc Dr. Alex DIESL, BGSU "Examples of Morphic Rings" 4:30 PM Honors MATH 295H Presentation 400 MSc Dr. Corneliu HOFFMAN, BGSU "Euler and Analysis Situs" ABSTRACT: Imagine a computer game that is played on the surface of a not so large planet that might not be spherical but possibly donut shaped or figure eight shaped and so on. Can you figure out its shape? You cannot lift off the planet. You can only use the minimap but can travel extensively on it and mark points and so on. This is the year of Euler's 300th birthday; see http://www.maa.org/euler/ Tuesday, September 11, 2007 11:00 AM Graduate Committee Meeting 400 MSc 1:00 PM Statistics Education Seminar 459 MSc Hope BARBERA, BGSU "On-Line MATH 115" 2:30 PM Analysis Seminar 459 MSc George TURCU, BGSU "Powers of Hypercyclic Functions for Some Classical Operators" 3:30 PM MATH 128/130 Instructors Meeting 400 MSc Wednesday, September 12, 2007 10:30 AM Statistics Group Meeting 459 MSc 3:30 PM Calculus Seminar 459 MSc "Writing in Calculus" Thursday, September 13, 2007 10:30 AM MATH 122 Instructors Meeting 400 MSc 10:45 AM MATH 112 Instructors Meeting 459 MSc 3:45 PM Foundational Math Committee 400 MSc 4:30 PM Lattice Ordered Groups Seminar 459 MSc Friday, September 14, 2007 12:00 Noon Calendar Information Due to Cyndi for next week's calendar 12:00 Noon Graduate Student Seminar 400 MSc Kevin DREES "C(X,Z)" 3:30 PM Refreshments served prior to the colloquium 3:45 PM Colloquium 459 MSc Prof. S. Ejaz Ahmed, University of Windsor "Shrinkage and Lasso/Lars and Related Estimation Strategies in Partially Linear Models" ABSTRACT: In this talk, I consider a partially linear model where the vector of coefficients in the linear part can be partitioned where first sub-vector is the coefficient vector for main effects (e.g. treatment effect, genetic effects) and the other is a vector for Śnuisanceą effects (e.g., age, lab). In this situation, inference about may benefit from moving the least squares estimate for the full model in the direction of the least squares estimate without the nuisance variables (Steinian shrinkage), or to drop the nuisance variables if there is evidence that they do not provide useful information (pre-testing). We investigate the asymptotic properties of Stein-type and pretest semiparametric estimators under quadratic loss and show that under general conditions a Stein-type semiparametric estimator improves on the full model conventional semiparametric least square estimator. We also consider a LASSO type estimator for partially linear models and give a Monte Carlo simulation comparison of theses estimators. The comparison shows that shrinkage method performs better than LASSO when the number of restriction on parameter space is large. Saturday, September 15, 2007 10:00A - 3:00P Tenured/Tenure Track Faculty Retreat 577 Foundation, Perrysburg, OH Sunday, September 16, 2007
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