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For this study, 9 parameters are used for both models to obtain a wider perspective of generating a proxy model.
Table 8 provides the variable range between maximum and minimum values for the uncertainty parameters used for generating a proxy model.
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Five remote sensing images of the Northwestern Iberian Peninsula, obtained with Landsat-5 TM, were used to generate a proxy for net primary production by combining the normalized difference vegetation index (NDVI) of each image to calculate a ΣNDVI index that could act as a potential indicator of some ecosystem services.
Using these variables we generate a proxy for labor market experience.
It must be noted that the RSM approach only considers completion parameters to generate a proxy model.
The reduced quadratic model initially generates a proxy model consisting of all quadratic terms and interaction terms.
A response surface modeling approach was applied to investigate the interaction between parameters and generate a proxy model for optimizing oil recovery and CO2 injectivity.
We enabled a Computer Modeling Group (CMG) workflow to use D-optimal design to implement response surface modeling, and the RSM polynomial fit will be of higher order, i.e., linear + quadratic + interaction parameters terms are used to generate a proxy model to validate the simulation results.
We then simulate spike trains from the model to generate a proxy dataset with coupling only on timescales <100 ms. The firing rates and inter-spike interval distributions of simulated spikes both match those from the original data.
We generated a proxy list based on a maximum basepair distance of 500 kb, which was the maximum distance that could be queried.
This was done using the cross-sectional data from Burkina Faso to generate a proxy for the human reservoir of infection at this specific time in this location (although it does not take into account how vector biting rate may vary with host age).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com