predict function for MaxEnt(Software R) -


i'm trying use predict function predict potencial occurrence points in space transfer. using dismo package loaded presence points in original space, 17 raster layers original space , 17 raster layer transfer space. rasters identicals in extent, grid resolution , dimension, differing in geographic coords. original space , transfer space located in different continents , have used kfold techinque partitioning of samples in training , testing.

i fit maxent model with:

me<-maxent(predictor, training)

but, can't project fit model in transfer space, returning:

pred<-predict(me,predictor2)     erro em .local(object, ...) : missing layers (or wrong names)

*predictors 1 , 2 in raster stack file

*all directories correctly choosen, , files found directory.

*both, stack contain same variable in each geographic space

that points 'wrong names' then. fix that

names(predictor2) <- names(predictor)

but make sure correct (that is, 2 rasterstack objects have same layers in same order), inspecting 

names(predictor2) names(predictor)

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