Halton and Hammersley Sequences in Multivariate Nonparametric Regression

by Rafajlowicz, E.; Schwabe R.


Preprint series: 04-20, Preprints

62K05 Optimal designs


Abstract: 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.

Keywords: experimental design, nonparametric regression, quasi-random sequences

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