Abstract
Good lattice point sets have desirable space-filling properties, and many designs with large L1-distance can be obtained by the leave-one-out good lattice point method (Zhou and Xu, 2015). However, there are negatively fully correlated columns in such a design. This is undesirable in the modeling of computer experiments. To overcome such a deficiency, we propose a class of designs based on the leave-one-out good lattice point method, whose columns can be divided into two groups, such that any two columns are column-orthogonal when they are from different groups and nearly column-orthogonal when they are in the same group. The new designs can also estimate the linear effects without being correlated with the second-order effects. Moreover, they have good stratification properties and their L1-distances are comparable with the corresponding designs in Zhou and Xu (2015).
Original language | English (US) |
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Pages (from-to) | 29-40 |
Number of pages | 12 |
Journal | Journal of Statistical Planning and Inference |
Volume | 185 |
DOIs | |
State | Published - Jun 1 2017 |
All Science Journal Classification (ASJC) codes
- Statistics and Probability
- Statistics, Probability and Uncertainty
- Applied Mathematics