🚀 go-pugleaf

Topic:    Principal Curves
Speaker:  Trevor Hastie
          Statistics and Data Analysis Group
          AT&T Bell Laboratories
          Murray Hill, New Jersey
Date:     Thursday, September 29, 1988, 4:00 p.m.
Place:    Sidney Smith Hall, room 2110, 100 St George St, University of Toronto

Abstract:
The first linear principal component of a p-dimensional point cloud provides
the line that minimizes the distance from the points to itself.  It is a one
dimensional summary of the data, but often a linear summary is inadequate.

Principal curves are smooth one dimensional curves that pass through the middle
of the data. They minimize the distance from the points, a non-linear summary 
of the data.  In practice the curves are estimated using smoothers and so 
their shape is suggested by the data.

After a brief introduction, I will show a short movie that illustrates
the curves and demonstrates an algorithm for fitting them.   This will be
followed by some technical definitions and results.  Finally, I will
briefly describe several areas of practical importance where the techniques
have been successfully applied.

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Coffee and tea will be served in the Delury Lounge (SS6006) at 3:30 p.m.