Pages that link to "Item:Q4932237"
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The following pages link to Using temporal variability to improve spatial mapping with application to satellite data (Q4932237):
Displaying 29 items.
- Multivariate spatio-temporal models for high-dimensional areal data with application to longitudinal employer-household dynamics (Q262346) (← links)
- Spatio-temporal statistical analysis of the carbon budget of the terrestrial ecosystem (Q290368) (← links)
- A comparison of spatial predictors when datasets could be very large (Q311779) (← links)
- Variable family size based spatial moving correlations model (Q505994) (← links)
- An overview on econometric models for linear spatial panel data (Q2023837) (← links)
- Discovering optimally representative dynamical locations (ORDL) in big multivariate spatiotemporal data: a case study of precipitation in Australia from space to ground sensors (Q2110042) (← links)
- Reduction problems and deformation approaches to nonstationary covariance functions over spheres (Q2180050) (← links)
- A scalable Bayesian nonparametric model for large spatio-temporal data (Q2184402) (← links)
- Bayesian inference of spatio-temporal changes of arctic sea ice (Q2226700) (← links)
- Pair-wise family-based correlation model for spatial count data (Q2278864) (← links)
- Comparing and selecting spatial predictors using local criteria (Q2348712) (← links)
- Monitoring abrupt changes in satellite time series by seasonal confidence interval of regression residuals (Q2818320) (← links)
- Dynamic Multiscale Spatiotemporal Models for Gaussian Areal Data (Q3107198) (← links)
- Spatial Statistical Data Fusion for Remote Sensing Applications (Q4648542) (← links)
- Dimension-Reduced Modeling of Spatio-Temporal Processes (Q4975634) (← links)
- A Fused Gaussian Process Model for Very Large Spatial Data (Q5065995) (← links)
- An Approach to Incorporate Subsampling Into a Generic Bayesian Hierarchical Model (Q5066475) (← links)
- Bayesian Hierarchical Models With Conjugate Full-Conditional Distributions for Dependent Data From the Natural Exponential Family (Q5146051) (← links)
- Estimating Spatial Changes Over Time of Arctic Sea Ice using Hidden 2×2 Tables (Q5377196) (← links)
- Spatio‐temporal smoothing and EM estimation for massive remote‐sensing data sets (Q5495689) (← links)
- Constructing valid spatial processes on the sphere using kernel convolutions (Q6069106) (← links)
- Modeling Nonstationarity in Space and Time (Q6079971) (← links)
- Modeling Temporally Evolving and Spatially Globally Dependent Data (Q6086581) (← links)
- A two-level variational algorithm in the Sobolev-Orlicz space to predict daily surface reflectance at LANDSAT high spatial resolution and MODIS temporal frequency (Q6175239) (← links)
- Spatial data fusion for large non-Gaussian remote sensing datasets (Q6540535) (← links)
- 30 years of space-time covariance functions (Q6602109) (← links)
- Spatial Statistical Downscaling for Constructing High-Resolution Nature Runs in Global Observing System Simulation Experiments (Q6621646) (← links)
- Spatiotemporal multiresolution modeling to infill missing areal data and enhance the temporal frequency of infrared satellite images (Q6625876) (← links)
- Spatio-temporal data fusion for massive sea surface temperature data from MODIS and AMSR-E instruments (Q6626131) (← links)
