Using temporal variability to improve spatial mapping with application to satellite data
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Publication:4932237
DOI10.1002/cjs.10063zbMath1349.62568OpenAlexW2046745272WikidataQ104697280 ScholiaQ104697280MaRDI QIDQ4932237
Noel Cressie, Tao Shi, Emily L. Kang
Publication date: 1 October 2010
Published in: Canadian Journal of Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1002/cjs.10063
aerosol optical depth (AOD)fine-scale variabilityfixed rank filtering (FRF)fixed rank kriging (FRK)multi-angle imaging spectroradiometer (MISR) instrumentspatial random effects (SRE) modelspatio-temporal random effects (STRE) modelvector autoregressive (VAR) process
Inference from spatial processes (62M30) Applications of statistics to environmental and related topics (62P12)
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Cites Work
- Statistical analysis of small-area data based on independence, spatial, non-hierarchical, and hierarchical models
- On semiparametric familial\,-\,longitudinal models
- Multiresolution models for nonstationary spatial covariance functions
- Fixed Rank Kriging for Very Large Spatial Data Sets
- Gaussian Predictive Process Models for Large Spatial Data Sets
- On Deriving the Inverse of a Sum of Matrices
- A dimension-reduced approach to space-time Kalman filtering
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