You can use the Durbin-Watson test in SPSS :)

Dear William,

it is really simple, just two lines of code. If you have loaded the "raster" package, the RasterLayer containing the predictions and the RasterLayer containing the occurrence (presence/background) data, then do the following:

1) calculate the difference between the predictions and the occurrence (i.e. the residuals). Please note that this calculation assumes that all non-presence raster cells (=background cells) are absences, which is not a valid assumption in the case of a presence-only dataset.

2) calculate the global Moran's I measure of the residuals. Please note that Moran's I, by definition, should be calculated using the rook's case weight matrix, hence, you should change the w parameter of function Moran() from its default value, which is queen's case.

Here is a sample code:

library(raster)

predictions = raster("file_name_of_predictions.tif")

occurrences = raster("file_name_of_occurrences.tif")

residuals = predictions - occurrences

Moran(x = residuals, w = matrix(data = c(0, 1, 0, 1, 0, 1, 0, 1, 0), nrow = 3, ncol = 3))

HTH,

Ákos

William Benjamin I recommend the GeoDa software, it is intuitive to use and since it is free software you will find manuals and tutorials.

https://geodacenter.github.io/download.html