Spatio-temporal covariates used to make predictive maps across the state of Kansas
Multivariate geostatistics is based on modelling all covariances between all possible combinations o...
Presented to the 12th Annual Symposium on Graduate Research and Scholarly Projects (GRASP) held at ...
Kriging and cokriging and their several related versions are techniques widely known and used in spa...
<p>Model statistics for Bayesian spatio–temporal covariate models evaluating county–level RMSF preva...
Environmental covariates used to predict the spatial distribution of soil organic carbon for the art...
<p>All data were mapped to a common geographic extent at 250-m resolution.</p><p>Covariates used as ...
Covariates used for the regression analysis and for making the infection risk map of the African Gre...
Field samples from Kansas of Rhopalosiphum padi, Schizaphis graminum, Sitobion avena, and Barley yel...
<p>Numerical summary of predictions overall and across several covariates by prediction error (km) a...
The file ‘state covariates.csv’ includes the percentage of nine habitat types (water, development, b...
student competitionPlatinum Sponsors * KU Department of Geography * KU Institute for Policy ...
<p>Mean values (SD) of covariates by location across all years from conservation grasslands in Minne...
<p>Final list of landscape-level habitat covariates modeled on probability of occupancy and coloniza...
We would like to thank Marc Genton and William Kleiber (hereafter, GK) for their informative review,...
Our goal is to create spatio-temporal models for predicting future gubernatorial elections. For a co...
Multivariate geostatistics is based on modelling all covariances between all possible combinations o...
Presented to the 12th Annual Symposium on Graduate Research and Scholarly Projects (GRASP) held at ...
Kriging and cokriging and their several related versions are techniques widely known and used in spa...
<p>Model statistics for Bayesian spatio–temporal covariate models evaluating county–level RMSF preva...
Environmental covariates used to predict the spatial distribution of soil organic carbon for the art...
<p>All data were mapped to a common geographic extent at 250-m resolution.</p><p>Covariates used as ...
Covariates used for the regression analysis and for making the infection risk map of the African Gre...
Field samples from Kansas of Rhopalosiphum padi, Schizaphis graminum, Sitobion avena, and Barley yel...
<p>Numerical summary of predictions overall and across several covariates by prediction error (km) a...
The file ‘state covariates.csv’ includes the percentage of nine habitat types (water, development, b...
student competitionPlatinum Sponsors * KU Department of Geography * KU Institute for Policy ...
<p>Mean values (SD) of covariates by location across all years from conservation grasslands in Minne...
<p>Final list of landscape-level habitat covariates modeled on probability of occupancy and coloniza...
We would like to thank Marc Genton and William Kleiber (hereafter, GK) for their informative review,...
Our goal is to create spatio-temporal models for predicting future gubernatorial elections. For a co...
Multivariate geostatistics is based on modelling all covariances between all possible combinations o...
Presented to the 12th Annual Symposium on Graduate Research and Scholarly Projects (GRASP) held at ...
Kriging and cokriging and their several related versions are techniques widely known and used in spa...
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