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comment Robust alternatives to Moran's I
@FC84, nothing's been published (other than what's on my web page). It might be while (if ever) before I attempt publishing any of this. I would recommend running your data through a series of power transformations until you find a power that symmetrizes your data if skew is a problem.
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comment Robust alternatives to Moran's I
@FC84, I revisited this issue last year and wrote up a proposed solution. But it needs vetting. I plan to offer a (much) reduced version of that write-up as an answer here at some point. Feel free to glean what you can from what I have. But use it with caution!
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comment Is median center more influenced than mean center by value outlier in ArcMap?
It may help to interpret the weight as a multiplier of points. If one point is assigned a weight of four, the software may interpret this as implying that four points occur at that same location. If this is the case, then it makes sense that the median would be more heavily influenced by a change in weight as opposed to distance.
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comment How to create an error map to support an average kernel density map?
@whuber, could you elaborate on (a) in your first paragraph? For example, are you referring to errors in data collection techniques that may persist across each forest gap (and therefore systematically manifest themselves in each KDE raster), or errors tied to the implementation of the focal function?
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comment How to implement bivariate Ripley's K function?
For your second inquiry, you might glean some inspiration from this answer. The shuffling of labels should be easy in Python. For spatial stats in Python you might want to look at PySAL.
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