BlasBenito / spatialRF

R package to fit spatial models with Random Forest
https://blasbenito.github.io/spatialRF/
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Some questions about the definition of the distance matrix #17

Open StoneWU1992 opened 1 year ago

StoneWU1992 commented 1 year ago

Dear Authors, 1.I would like to know how the distance matrix is calculated in this method and what are his units (metres or kilometres)? 2.Why does this spatial method fail when I define the distance matrix as a geographic distance matrix? 3.In a large computer memory we train this model with a large amount of data, which would take much longer. We look forward to hearing from you.

StoneWU1992 commented 1 year ago

In addition a warning message appeared after I interrupted the run: Warning message: In auto_cor(x = spatial.predictors.df, preference.order = colnames(spatial.predictors.df), : These columns have zero variance and might cause issues: spatial_predictor_300_1, spatial_predictor_300_2, spatial_predictor_300_3, spatial_predictor_300_4, spatial_predictor_300_5, spatial_predictor_300_6, spatial_predictor_300_7, spatial_predictor_300_8, spatial_predictor_300_9, spatial_predictor_300_10, spatial_predictor_300_11, spatial_predictor_300_12, spatial_predictor_300_13, spatial_predictor_300_14, spatial_predictor_300_15, spatial_predictor_300_16, spatial_predictor_300_17, spatial_predictor_300_18, spatial_predictor_300_19, spatial_predictor_300_20, spatial_predictor_300_21, spatial_predictor_300_22, spatial_predictor_300_23, spatial_predictor_300_24, spatial_predictor_300_25, spatial_predictor_300_26, spatial_predictor_300_27, spatial_predictor_300_28, spatial_predictor_300_29, spatial_predictor_300_30, spatial_predictor_300_31, spatial_predictor_300_32, spatial_predictor_300_33, spatial_predictor_300_34, spatial_predictor_300_35, spatial_predictor_300_36, spatial_predicto [... truncated]

admahood commented 1 year ago

Hey Authors, Thanks for the great package. I think it would be good to include some basic code to create a distance matrix from the xy object in the tutorial. I say this because I know it's really easy, but I always forget how to do it and there's so many different spatial packages out there.