ENAR Austin March 20-23, 2004

Title:  Remarks on Mixtures of Regressions


Abstract:

Robust regression techniques can help with messy data
contaminated by outliers.  A related problem occurs when
the data represent a mixture of regressions, perhaps
with significant overlap.  We examine how kernel methods,
minimum distance parametric modeling, and mixture models
may be used to address such data.