In my analysis, I have calculated elephant fence breaks per 100m (along a 55km electrified fence). Because of the skewed distribution of fence breaks /100m (many sections with 0 breaks , one section with 38 breaks). i have binary coded the outcome variable (i..e. each 100m section) to have breaks/no breaks
I have generated a number of independent variables to predict the occurrence of breaking (e.g distance to crops, water, voltage of the fence etc). However I have found (using a Runs test and in ArcGIS) that the occurrence of breaks/no breaks (and break count per 100m) is spatially autocorrelated. Therefore the predictive ability of my logistic regression model may be compromised: elephants may simply break near to where they have previously broken. I feel I need to capture this in my model.
Similar analyses assessing the occurrence of crop raids/ no crop raids in a landscape (represented as a raster) have addressed this problem by generating an autocovariate term which is the euclidean distance weighted mean of all 8 surrounding cells in the raster. The autocovariate term is then treated as an independent variable in the regression model
However I am not dealing with a raster but with lengths of a vector. Can I calculate the autocovariate to introduce into my logistic regression model by calculating the euclidean distance weighted mean of the break counts of the two neighbouring sections?
If so, how do I do this in ArcGIS?
Thanks in advance,
George Aike
