Optimization and Systems Theory Seminar
Friday, February 6, 1998, 11.00-12.00, Room 3721,
Department of Mathematics
Luleå University of Technology
Algorithms for M-estimates
When fitting a model function to data, the least squares criterion is
traditionally used. Unfortunately a least squares estimate is very sensitive=
to errors in data. During the last three decades there has been a lot
of intere= st in finding good alternatives to least
squares. M-estimates, to where e.g. the Huber estimate belong, is an
important class of estimates within so called robust regression.
I will give some statistical background to the computational problems
considered. The main features of some algorithms designed to compute
M-estimates will be presented. Also non-linear models will be treated.
Calendar of seminars
Last update: January 26, 1998 by