Variable informativeness in discriminant analysis
Tatjana Pavlenko
Department of Mathematical Statistics,
Lund Institute of Technology,
Lund University,
1998
ISSN 02811944
ISRN LUNFD6/NFMS3194SE

Abstract:

The performance of discrimination, measured by overall conditional error
rate, is effected by variable informativeness. Our point is to evaluate this
effect in an asymptotic setup. We suggest to regard the informativeness of
a set of variables as a random value with a proper distribution. In order
to carry out the effect of informativeness on discrimination we introduce
the weighted discriminant function. New asymptotic results for the error
rate yielded by the weighted discriminant function are obtained in a sequence
of discrimination problems. The optimal type of the weight function for which
the overall conditional error rate achieves the minimum value is found.


Key words:

discrimination problem, growing dimension asymptotics, weighted discriminant
function, conditional error rate
