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5. Matrix-free REML for Linear Spatial-temporal State-space Models using H-likelihood Methods

Matrix-free REML for Linear Spatial-temporal State-space Models using H-likelihood Methods

来源 :上海交通大学 | 被引量 : 0次 | 上传用户：xkt376

【摘 要】

：

We combines Besags spatial-temporal Gaussian autoregressions within a state-space model and presents a novel matrix-free h-likelihood method for statistical inference.

【作 者】

：

Chunxiao Wang Debashis Mondal 

【机 构】

：

Statistics Department,Oregon State University,97330,USA

【出 处】

：

上海交通大学

【发表日期】

：

2016年4期

【关键词】

：

H-likelihood Kalman filter Lanczos algorithm Matrix-free computation State space 

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　　We combines Besags spatial-temporal Gaussian autoregressions within a state-space model and presents a novel matrix-free h-likelihood method for statistical inference.

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