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  5. Functional Inverted-Wishart for Massive Multivariate Spatial Modeling

Functional Inverted-Wishart for Massive Multivariate Spatial Modeling

来源 :上海交通大学 | 被引量 : 0次 | 上传用户：fslihua
【摘 要】
：
Multivariate spatial analysis often relies on a low-dimensional latent representation of fac-tors or dictionary entries,often of Gaussian processes.Despite of the efficiency,this can be unrealistic du
【作 者】
：
Leo L.Duan Xia Wang Rhonda Szczesniak 
【机 构】
：
Johns Hopkins University,Baltimore,MD 21218,USA U
【出 处】
：
上海交通大学
【发表日期】
：
2016年4期
【关键词】
：
Covariance Convolution Outcome-based Approach Inverted-Wishart Sparse Tensor Fou 
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　　Multivariate spatial analysis often relies on a low-dimensional latent representation of fac-tors or dictionary entries,often of Gaussian processes.Despite of the efficiency,this can be unrealistic due to the restricted d-many choices for the diverse patterns in each outcome,which is of important interests in environmental systems.
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