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 . However I have found (using Moran's I) 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 spatial analyses assessing the occurrence of an event/no event 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 100m sections of fence? If so, how do I do this in ArcGIS?
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