Low-Rank Representations for Spatial Processes-Reference-Cited by-同舟云学术

Low-Rank Representations for Spatial Processes

Published:2010-03-19 Issue: Volume: Page:107-118
ISSN:2154-5944
Container-title:Chapman & Hall/CRC Handbooks of Modern Statistical Methods
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Author:

Wikle Christopher

Publisher

CRC Press

Reference26 articles.

1. Long-Lead Prediction of Pacific SSTs via Bayesian Dynamic Modeling

2. Integral Equation Representation for Factor Analysis

3. C.E. Buell, The topography of empirical orthogonal functions, Fourth Conference on Probability and Statistics in Atmospheric Science, American Meteorological Society, 188-193. 1975.

4. A dynamic process convolution approach to modeling ambient particulate matter concentrations

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