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Hello everyone, I have the following problem: My analysis includes many predictor variables (>50) in the form of raster maps (asc), but I am trying to avoid having to type all their names over and over again in the analysis...
Dear all, I have built glm models based on presences/absences and a number of predictor maps and would like to compute habitat suitability based on the modelled coefficients. I thought this is pretty straight forward and wanted to use...
Dear all, thanx for the quick reply but your ideas have not gotten me further unfortuantely.. after implementing the idea from Thierry my code looks like that now: #b00all is the dataframe with only element used for model fitting #variables...
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