Zurück zu den Preprints des Jahres 2004


Halton and Hammersley Sequences in Multivariate Nonparametric Regression

by Rafajlowicz, E., Schwabe R..

Series: 2004-20, Preprints

62K05 Optimal designs

The present paper generalizes results
by Rafajlowicz and Schwabe (2003)
for quasi least squares estimators
in additive regression
to a general multivariate regression setup.
Equidistributed sequences of Halton or
Hammersley type provide consistent regression estimators
with a satisfactory rate of convergence.
As those sequences are easy to construct
they can serve as suitable experimental designs.
Optimal generators for the Halton and Hammersley sequences
are found by exhaustive search.

experimental design, nonparametric regression, quasi-random sequences