منابع مشابه
Sliced space - filling designs
We propose an approach to constructing a new type of design, a sliced space-filling design, intended for computer experiments with qualitative and quantitative factors. The approach starts with constructing a Latin hypercube design based on a special orthogonal array for the quantitative factors and then partitions the design into groups corresponding to different level combinations of the qual...
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New types of designs called nested space-filling designs have been proposed for conducting multiple computer experiments with different levels of accuracy. In this article, we develop several approaches to constructing such designs. The development of these methods also leads to the introduction of several new discrete mathematics concepts, including nested orthogonal arrays and nested differen...
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Nested space-filling designs are nested designs with attractive lowdimensional stratification. Such designs are gaining popularity in statistics, applied mathematics and engineering. Their applications include multifidelity computer models, stochastic optimization problems, multi-level fitting of nonparametric functions, and linking parameters. We propose methods for constructing several new cl...
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Latin Hypercube Sampling (LHS) and Jittered Sampling (JS) both achieve better convergence than standard Monte Carlo Sampling (MCS) by using stratification to obtain a more uniform selection of samples, although LHS and JS use different stratification strategies. The “Koksma-Hlawka-like inequality” bounds the error in a computed mean in terms of the sample design’s discrepancy, which is a common...
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ژورنال
عنوان ژورنال: Journal of Simulation
سال: 2013
ISSN: 1747-7778,1747-7786
DOI: 10.1057/jos.2013.8