摘要翻译:
基于火箭助推器设计的计算机实验,本文探讨了将平稳高斯过程与树状划分相结合的非平稳建模方法。划分是处理非平稳性的一种简单而有效的方法。详细描述了使该方法有效的方法学发展和统计计算细节。除了提供对火箭助推器模拟器的分析,我们的方法被证明在其他领域是有效的。
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英文标题:
《Bayesian treed Gaussian process models with an application to computer
modeling》
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作者:
Robert B. Gramacy and Herbert K. H. Lee
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最新提交年份:
2008
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分类信息:
一级分类:Statistics 统计学
二级分类:Methodology 方法论
分类描述:Design, Surveys, Model Selection, Multiple Testing, Multivariate Methods, Signal and Image Processing, Time Series, Smoothing, Spatial Statistics, Survival Analysis, Nonparametric and Semiparametric Methods
设计,调查,模型选择,多重检验,多元方法,信号和图像处理,时间序列,平滑,空间统计,生存分析,非参数和半参数方法
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一级分类:Statistics 统计学
二级分类:Applications 应用程序
分类描述:Biology, Education, Epidemiology, Engineering, Environmental Sciences, Medical, Physical Sciences, Quality Control, Social Sciences
生物学,教育学,流行病学,工程学,环境科学,医学,物理科学,质量控制,社会科学
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一级分类:Statistics 统计学
二级分类:Computation 计算
分类描述:Algorithms, Simulation, Visualization
算法、模拟、可视化
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英文摘要:
Motivated by a computer experiment for the design of a rocket booster, this paper explores nonstationary modeling methodologies that couple stationary Gaussian processes with treed partitioning. Partitioning is a simple but effective method for dealing with nonstationarity. The methodological developments and statistical computing details which make this approach efficient are described in detail. In addition to providing an analysis of the rocket booster simulator, our approach is demonstrated to be effective in other arenas.
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PDF链接:
https://arxiv.org/pdf/710.4536