Showing a limited preview of this publication:
The spectral test provides a reliable measure for lattice assessment and can be computed very efficiently. It has extensively been applied to find good lattices for several MC and QMC applications. In order to enable comparisons across dimensions, a normalized spectral test is widely used. We empirically demonstrate significant shortcomings of this normalization in high dimensions, discuss the empirical distribution of the normalized spectral test values, and propose a new normalization strategy. The new normalization is shown to give more reliable results, especially concerning the comparability of the values accross dimensions.
Keywords: Monte Carlo Simulation; pseudo-random numbers; LCG; spectral test; parameter search; lattice rules; quasi Monte Carlo Methods
Published Online: 2008-05-09
Published in Print: 2004-12
© de Gruyter 2004
