I have a model from which I am attempting to create a predictive map (in GIS, but I'm aware of some options in R). The response values are constrained to [0,1] using an offset term in the model (see the full model below) and as such, raster values should also have the same constraints.
I believe the syntax in Raster Calculator is correct, but the output values aren't constrained to [0,1]. My guess at the moment is that this is because I scaled the variables around a mean of 0 and standard deviation of 1 prior to model building. Is my best bet of achieving the predictive map to also scale the rasters in GIS or R? If so, how?
Model syntax in Raster Calculator is as follows:
Ln(57064) + (-0.10872 * "var1"^2)+ (0.02844* "var2"^2)+(-0.03848 * "var3"^2)+ (0.05726*"var4") +(0.06462*"var5"^2)+(- 0.42450*"var6"^2)
أكثر...
I believe the syntax in Raster Calculator is correct, but the output values aren't constrained to [0,1]. My guess at the moment is that this is because I scaled the variables around a mean of 0 and standard deviation of 1 prior to model building. Is my best bet of achieving the predictive map to also scale the rasters in GIS or R? If so, how?
Model syntax in Raster Calculator is as follows:
Ln(57064) + (-0.10872 * "var1"^2)+ (0.02844* "var2"^2)+(-0.03848 * "var3"^2)+ (0.05726*"var4") +(0.06462*"var5"^2)+(- 0.42450*"var6"^2)
أكثر...