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If the size and shape of the SDEs were more closely aligned … then you could say that the distributions were similar and that the surveyed and un-surveyed stores are part of the same “landscape.” Since the ellipse for the un-surveyed locations is much smaller than the ellipse for the surveyed locations, this seems to indicate the opposite … that the un-surveyed locations are actually not representative of the entire county/study area. The fact that all of the un-surveyed locations fall into the surveyed ellipse is not sufficient evidence, however … The surveyed ellipse contains the ellipse for the un-surveyed locations. This is the one bit of evidence that the surveyed locations are representative of the landscape. How were the surveyed locations picked? This is a very important question to answer in order to be confident that the information collected from the survey is representative of all the tobacco retail in the county. If there was no bias in how the department picked who was and wasn’t going to be surveyed – that would also be evidence. If all of the un-surveyed locations are within x distance of a surveyed location, then you would need to provide justification that the spatial context for locations at the farthest distances would be homogeneous … it looks like there are surveyed locations very close to every un-surveyed location except 2. Can you provide any evidence that indicates that those locations would not be different from their closest surveyed locations or from other surveyed locations in the study area? Schools are shown on your map. Are they important to the analysis? If they are then it might be helpful to ensure that surveying around each school meets some threshold to give confidence that the un-surveyed locations are not biasing the sample. Example: for all schools at least 50% of establishments within 1 mile were surveyed. Those that did not meet this criteria were excluded from the analysis. Hope this helps!
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11-09-2015
02:43 PM
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Hi Richard, Did you try using the updated toolbox that is attached above? -Jenora
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10-26-2015
09:25 AM
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Also ... I don't know what the question that you are trying to answer is, but these sample script tools eventually evolved into the tools that are in our Space Time Pattern Mining toolbox. In 10.3, Create Space Time Cube aggregates events into bins which can be then analyzed with Emerging Hot Spot Analysis. It might be valuable (and lots of fun) to check those out as well. Hope that was helpful. -Jenora
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05-18-2015
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Hi Tracy, We tweaked a few things in 10.3 that caused issues with the sample scripts. Here's an updated version that should work Thanks for catching that. -Jenora
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05-18-2015
04:54 PM
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Mmmm... not quite exactly, but a letter S was definitely the problem
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05-13-2015
04:01 PM
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I'm glad they got it figured out for you! We found a typo in the code that handles projection conversion. The majority use meters and feet and it turns out we didn't have a test for miles and we missed it. Good catch and apologies for the inconvenience... we have fixed this for future releases. -Jenora
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05-13-2015
03:37 PM
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Thanks! I was able to repro ... Investigating now ...
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05-13-2015
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Hey John, Can you send me a screenshot of the tool parameters you were using or provide a repro with data so that I can have a look? Tracebacks are no good, we'll figure this out ... jdacosta@esri.com Thanks, Jenora
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05-13-2015
11:05 AM
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Hi Amanda, Right now, the Space Time Pattern Mining tools are for use with incident data only, which are generally always points although there are certainly exceptions. If you were looking at forest fires or flooding events, which are typically represented as polygons, you could use a centroid or point to represent the event/occurrence. However, boundaries such as census blocks are not true events and it probably wouldn't make sense. What we are probably interested in in that case is how the associated attribute is changing over time. We are currently working on some very exciting ways to aggregate and analyze attributes in the cube structure, but they are not quite ready yet Can you tell me more about the question that you are trying to answer? I could maybe suggest different way ... Hope that helps, Jenora
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03-27-2015
10:30 AM
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Hey Zoe! Sorry it took me so long to see your issue! Can you tell me what version of the software you are using (10.2, 10.2.1 or 10.2.2)? I'd like to try to repro this error. We never like to see tracebacks ... it looks like it may be a setup issue. Best, Jenora Spatial Statistics, Esri
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03-23-2015
11:25 AM
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Hmm ... I didn't encounter either of those problems. Two quick questions ... 1. Did you start from a blank map? "Failed to alter the spatial reference" can happen if the dataset is read-only or being locked by another application. If it was active in another map or project, that could have been the issue... 2. At what point are you trying to view the attribute table? If the Project tool fails and the attribute table of the layer it was trying to create is empty, that would be expected as the Project tool did not complete. If you cannot view the attribute table after Display XY Data ... that would be a different issue. This article may have some clues as to why you are not seeing the attributes as expected: 27589 - Import XY data tables to ArcMap and convert the data to a shapefile I guess best case is that you maybe had another map with the same layers open and that is what is causing both issues. Let me know how it goes. Jenora
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03-23-2015
11:05 AM
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Jose, I just took a quick look, here’s what I did starting from a blank map: Add a basemap, add Zonas – they should line up. Add the Event table to map, right click the Event table and choose Display XY Data. In the Display XY Data pop out box, under Coordinate System of Input Coordinates, click edit and set the coordinate system to GCS_WGS_1984. Click OK and the points should show on top of your polygons. Use the tool Project (Data Management) to project to WGS_1984_UTM_Zone_19N ... Then they shouldn't go anywhere. Let me know if that works ... Best, Jenora
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03-19-2015
04:22 PM
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Eight neighbors comes from the suggestion of Getis and Ord documented in their 1992 paper, The Analysis of Spatial Association by Use of Distance Statistics (link below). They were using Queen’s Case just like the graphic from Kishor. Mark Janikas also did empirical testing and found that eight nearest neighbors was generally enough neighbors to assure the test statistic was asymptotically normal for skewed data. This was accomplished by comparing the standard z-score with the pseudo p-value obtained via the permutation approach. He assessed the test statistic with a variety of distributions … Exponential, Poisson etc. It is important to remember that 8 is a suggestion and not a magic number. The distance band value that you choose should make sense in the context of the question you are asking. Here is the link to the paper: http://onlinelibrary.wiley.com/doi/10.1111/j.1538-4632.1992.tb00261.x/abstract Hope this was helpful.
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