Andreas Buja's Home Page

Room: 471 JMHH
Office: (215) 898-8236, Fax: (215) 898-1280, Dept: (215) 898-8222
Email: click here for an image of the address
Curriculum vitae: [.pdf] (a more fun alternative from the 2004/5 MBA guide))

Teaching:

• STATISTICS 101, Spring 2008: Introductory Business Statistics (I)
  Syllabus. Here is the webCafe site for this class. Go to "STAT 101" and your section.

  (Spring 2007 class: Here are the modules in case you lost access to webCafe.)

• STATISTICS 541, Statistical Methods, Fall 2007 (class web page)

  STATISTICS 541 has switched from spring to fall.
  This amounts to a switch with STATISTICS 540 (Statistical Computing)
  which is now taught in spring as STATISTICS 542.

• STATISTICS 102, Spring 2006: Introductory Business Statistics (II) (syllabus)

• STATISTICS 621, Fall 2003: Business Analysis with Regression

• STATISTICS 102, Spring 2003: Introductory Business Statistics (II)

• STATISTICS 540, Fall 2002: Statistical Computing
  See the class web page.

Current Interests:

• Model checking with parametric bootstrap: I brought this up back in 2004 in a discussion of a paper by Andrew Gelman who does the same with a posterior predictive approach. Here are Gelman's JCGS article, followed by my discussion, and his rejoinder.
  The reason for posting this now is that a few of us in the department are currently discussing model diagnostics.

• Lisha Chen's thesis paper:
  Local Multidimensional Scaling for Nonlinear Dimension Reduction, Graph Layout and Proximity Analysis [.pdf]

• On a topic in marketing, joint with N. Eyuboglu:
  Quasi-Darwinian Selection in Marketing Relationships [.pdf]
  Journal of Marketing, Oct 2007, featured JM blog article and a finalist for JM's 2007 Harold H. Maynard Award.
  Along with the paper go a few scenario calculations that are not included in the article: [.pdf]

• Here is a paper that started out as work on boosting but turned into something different, joint with Werner Stuetzle and Yi Shen:
  Loss Functions for Binary Class Probability Estimation: Structure and Applications. (Former title: Degrees of Boosting) [.pdf] (under revision)
  Yi Shen's 2005 Ph.D. thesis on cost-weighted class probability estimation [pdf]

• On a simple modification of boosting, joint with David Mease and Adi Wyner:
  Cost-Weighted Boosting with Jittering and Over/Under-Sampling: JOUS-Boost [pdf]
  (Journal of Machine Learning Research 8 (Mar), 409-439, 2007)

• A paper on bagging, joint with Werner Stuetzle:
  Observations on Bagging (Statistica Sinica 2006, Special Issue on Machine Learning, 16 (2), 323--352 (2006)) [pdf]

  A preliminary version and a companion paper which I keep posted because others have started referring to them:
  The Effect of Bagging on Variance, Bias, and Mean Squared Error [.pdf] PPT slides,
  Smoothing Effects of Bagging [.pdf]

• A paper on the use of simulation for simultaneous inference, with Wolfgang Rolke:
  Calibration for Simultaneity: (Re)Sampling Methods for Simultaneous Inference with Applications to Function Estimation and Functional Data [.pdf, 1.7MB] (under revision)

• Talk given at the Joint Statistics Meetings 1999, on the possibility of valid inference in exploratory data analysis, with Di Cook:
  Inference for Data Visualization [.pdf]

• Two papers on MDS:
  • Visualization Methodology for Multidimensional Scaling [pdf]
    A. Buja and D.F. Swayne; J. of Classification, 19, 7-43, 2002.
  • Interactive Data Visualization with Multidimensional Scaling [pdf] (to appear in JCGS, 2008)
    joint with Deborah Swayne, Michael Littman, Nate Dean, Heike Hofmann, and Lisha Chen.

• Two papers on special topics in high-dimensional data visualization, joint with Di Cook, Dan Asimov, and Catherine Hurley:
  • Computational Methods for High-Dimensional Rotations in Data Visualization [pdf]
    Appeared in "Handbook of Statistics", eds. E. Wegman, C. R. Rao.
  • Theory of Dynamic Projections in High-Dimensional Data Visualization [pdf] (submitted)
  An older version that had both papers in one should be considered out of date.

• Visual Comparison of Datasets using Mixture Decompositions [.pdf]
  Alan Gous and Andreas Buja; Journal of Computational and Graphical Statistics, 13 (1), 1-19 (2004).
  (We are permitted to post the color version of this paper. The printed version is b/w with gray-scale figures.)

• A paper on classification and regression trees with a datamining orientation:
  Data Mining Criteria for Tree-Based Regression and Classification [.ps.gz]
  A. Buja and Y.-S. Lee; Proceedings of KDD 2001, 27--36.

On writing:

• The Science of Scientific Writing by Gopen and Swan [HTML] [.pdf]]