Zobrazeno 1 - 10
of 87
pro vyhledávání: '"Lin, C. Devon"'
Publikováno v:
Journal on Uncertainty Quantification, 9(2), 333-353 (2021)
Computer experiments with both quantitative and qualitative (QQ) inputs are commonly used in science and engineering applications. Constructing desirable emulators for such computer experiments remains a challenging problem. In this article, we propo
Externí odkaz:
http://arxiv.org/abs/2203.10130
Publikováno v:
Bernoulli, 25, 2163-2182 (2019)
Recent researches on designs for computer experiments with both qualitative and quantitative factors have advocated the use of marginally coupled designs. This paper proposes a general method of constructing such designs for which the designs for qua
Externí odkaz:
http://arxiv.org/abs/2203.06340
Orthogonal array, a classical and effective tool for collecting data, has been flourished with its applications in modern computer experiments and engineering statistics. Driven by the wide use of computer experiments with both qualitative and quanti
Externí odkaz:
http://arxiv.org/abs/2203.06336
Computer experiments with both qualitative and quantitative input variables occur frequently in many scientific and engineering applications. How to choose input settings for such experiments is an important issue for accurate statistical analysis, u
Externí odkaz:
http://arxiv.org/abs/2203.06335
Autor:
Lin, C. Devon, Tang, Boxin
Publikováno v:
Handbook of Design and Analysis of Experiments, Bingham, D., Dean, A., Morris, M., and Stufken, J. ed. 593-626, CRC Press (2015)
This chapter discusses a general design approach to planning computer experiments, which seeks design points that fill a bounded design region as uniformly as possible. Such designs are broadly referred to as space-filling designs.
Externí odkaz:
http://arxiv.org/abs/2203.06334
Regularized linear models, such as Lasso, have attracted great attention in statistical learning and data science. However, there is sporadic work on constructing efficient data collection for regularized linear models. In this work, we propose an ex
Externí odkaz:
http://arxiv.org/abs/2104.01673
Computer experiments with both qualitative and quantitative factors are widely used in many applications. Motivated by the emerging need of optimal configuration in the high-performance computing (HPC) system, this work proposes a sequential design,
Externí odkaz:
http://arxiv.org/abs/2101.02206
Computer simulators are nowadays widely used to understand complex physical systems in many areas such as aerospace, renewable energy, climate modeling, and manufacturing. One fundamental issue in the study of computer simulators is known as experime
Externí odkaz:
http://arxiv.org/abs/1902.01011
Design of experiments is a fundamental topic in applied statistics with a long history. Yet its application is often limited by the complexity and costliness of constructing experimental designs, which involve searching a high-dimensional input space
Externí odkaz:
http://arxiv.org/abs/1804.02089
Publikováno v:
Annals of Statistics 2010, Vol. 38, No. 3, 1460-1477
We develop a new method for constructing "good" designs for computer experiments. The method derives its power from its basic structure that builds large designs using small designs. We specialize the method for the construction of orthogonal Latin h
Externí odkaz:
http://arxiv.org/abs/1010.0328