Hierarchical Factor Models for Large Spatially Misaligned Data: A Low‐Rank Predictive Process Approa...
Hierarchical Factor Models for Large Spatially Misaligned Data: A Low‐Rank Predictive Process Approach
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Full title
Author / Creator
Publisher
United States: Blackwell Publishers
Journal title
Language
English
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Publisher
United States: Blackwell Publishers
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Scope and Contents
Contents
This article deals with jointly modeling a large number of geographically referenced outcomes observed over a very large number of locations. We seek to capture associations among the variables as well as the strength of spatial association for each variable. In addition, we reckon with the common setting where not all the variables have been obser...
Alternative Titles
Full title
Hierarchical Factor Models for Large Spatially Misaligned Data: A Low‐Rank Predictive Process Approach
Authors, Artists and Contributors
Author / Creator
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Record Identifier
TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_4466112
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_4466112
Other Identifiers
ISSN
0006-341X
E-ISSN
1541-0420
DOI
10.1111/j.1541-0420.2012.01832.x
