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Correlations among some parameters of coarse-grained soils - the multivariate probability distribution model

机译:粗粒土壤中一些参数的相关性 - 多元概率分布模型

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A multivariate probability distribution model for seven parameters of coarse-grained soils is constructed based on the SAND/7/2794 database that was compiled by the authors. It is shown that the multivariate probability distribution captures the correlation behaviors in the database among the seven parameters. This multivariate distribution model serves as a prior distribution model in the Bayesian analysis and can be updated into the posterior distribution of the design soil parameter when multivariate site-specific information is available. It is shown that this Bayesian analysis is conceptually similar to what is routinely carried out in practice, which utilizes information from comparable sites to supplement limited site-specific information. The resulting posterior distribution from Bayesian analysis merely combines different uncertainties associated with different sources of "correlated" information in a more consistent way. In this paper, the parameters for the posterior distribution of the design soil parameter are summarized into engineer-friendly tables (Tables 9 and 10) so that engineers do not need to conduct the actual Bayesian analysis. Caution should be taken in extrapolating the results of this paper to cases that are not covered by SAND/7/2794, because the resulting posterior distribution can be misleading. This caveat applies to conventional regression equations as well.
机译:基于作者编制的SAND/7/2794数据库,建立了粗粒土七个参数的多元概率分布模型。结果表明,多元概率分布捕捉了数据库中七个参数之间的相关行为。该多变量分布模型作为贝叶斯分析中的先验分布模型,可在多变量场地特定信息可用时更新为设计土壤参数的后验分布。研究表明,这种贝叶斯分析在概念上类似于实践中经常进行的分析,即利用可比场地的信息来补充有限的场地特定信息。贝叶斯分析得到的后验分布只是以更一致的方式将与不同“相关”信息源相关的不同不确定性结合起来。在本文中,设计土壤参数的后验分布参数总结为工程师友好的表格(表9和表10),以便工程师不需要进行实际的贝叶斯分析。在将本文结果外推到SAND/7/2794未涵盖的情况时,应谨慎行事,因为由此产生的后验分布可能会产生误导。这个警告同样适用于传统的回归方程。

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