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Bridge Designs for Modeling Systems With Low Noise.
- Source :
-
Technometrics . May2015, Vol. 57 Issue 2, p155-163. 9p. - Publication Year :
- 2015
-
Abstract
- For deterministic computer simulations, Gaussian process models are a standard procedure for fitting data. These models can be used only when the study design avoids having replicated points. This characteristic is also desirable for one-dimensional projections of the design, since it may happen that one of the design factors has a strongly nonlinear effect on the response. Latin hypercube designs have uniform one-dimensional projections, but are not efficient for fitting low-order polynomials when there is a small error variance.D-optimal designs are very efficient for polynomial fitting but have substantial replication in projections. We propose a new class of designs that bridge the gap betweenD-optimal designs andD-optimal Latin hypercube designs. These designs guarantee a minimum distance between points in any one-dimensional projection allowing for the fit of either polynomial or Gaussian process models. Subject to this constraint they areD-optimal for a prespecified model. [ABSTRACT FROM PUBLISHER]
- Subjects :
- *NOISE
*GAUSSIAN distribution
*STATISTICS
*MATHEMATICS
*GEOMETRY
Subjects
Details
- Language :
- English
- ISSN :
- 00401706
- Volume :
- 57
- Issue :
- 2
- Database :
- Academic Search Index
- Journal :
- Technometrics
- Publication Type :
- Academic Journal
- Accession number :
- 108330789
- Full Text :
- https://doi.org/10.1080/00401706.2014.923788