Oberwolfach Seminar: Semiparametric and Nonparametric Regression

October 18th - October 24th, 2009
Raymond Carroll, College Station
Ciprian Crainiceanu, Baltimore
Matthew Wand, Wollongong
Semiparametric regression is concerned with the flexible nearly nonparametric incorporation of nonlinear functional relationships in regression analyses. Assuming only a basic familiarity with ordinary regression, this short-course explains the techniques and benefits of semiparametric regression in a concise and modular fashion. Spline functions, linear mixed models and Bayesian hierarchical models are shown to play an important role in semiparametric regression. There will be a strong emphasis on implementation in R and BUGS.

Besides learning about modern semiparametric and nonparametric regression, students in the course will be exposed to the linear mixed model in a unique way.

Topics Covered

Software SemiPar

Suggested Text
Semiparametric Regression by David Ruppert, Matthew P. Wand and Raymond J. Carroll (Cambridge University Press, 2003).

This book is available in paperback. See the book web site and a book review by Michael R. Chernick

See also
Crainiceanu, C., Ruppert, D. and Wand, M.P.:
Bayesian Analysis for Penalized Spline Regression Using WinBUGS.
Volume 14, 2005, Issue 14 of Journal of Statistical Software.

Deadline for applications
September 1st, 2009

The seminars take place at the Mathematisches Forschungsinstitut Oberwolfach. The number of participants is restricted to 24. The Institute covers accommodation and food. Travel expenses cannot be reimbursed. Applications including

should be sent as hard copy or by e-mail (.ps or .pdf file) to:

    Prof. Dr. Gert-Martin Greuel
    Universität Kaiserslautern
    Fachbereich Mathematik
    Erwin Schrödingerstr.
    67663 Kaiserslautern, Germany

Mathematisches Forschungsinstitut Oberwolfach   updated: December 9th, 2008