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This is a great question that we get a lot! At this time logistic regression is not available in ArcGIS, but we do have a sample script available that helps you run logistic regression using the R statistical package right from inside ArcMap. You can find the sample script here .
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12162011
02:50 PM

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Hi Oliver, Great question! Actually, we've got an awesome sample script for ArcGIS 10 that does exactly what you're asking for. It is called Exploratory Regression and it tests all combinations of your explanatory variables for all of the assumptions of OLS (including spatial autocorrelation of the residuals). You can find it here: Supplementary Spatial Statistics Toolbox . Also, Exploratory Regression is going to be part of core starting with ArcGIS 10.1, so if you'd like to try the latest version of the tool you might want to consider joining the Beta Program .
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12022011
08:54 AM

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Hi Stephanie, If you want to learn more about Hot Spot Analysis and all of the Spatial Statistics tools, our resources page: http://esriurl.com/spatialstats has tons of short videos, tutorials, sample scripts, and lots of other stuff that should help you get started!
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11172011
08:32 AM

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Hi Gina, Thanks so much for being willing to share your data with us so that we can figure this out! My email address is lrosenshein@esri.com . Please send over your data, as well as a screenshot of the parameters you're choosing, and any additional information that might be useful. I look forward to solving this problem and getting you moving forward! Lauren Rosenshein Geoprocessing Product Engineer
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11152011
08:14 AM

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Hi Antonio, To start with, it definitely sounds like you're on the right track by using the Spatial Autocorrelation tool to figure out a good distance to use for your Cluster and Outlier Analysis. Actually, there is a sample script in the resource center that does this analysis for you (and has a lot of documentation about how to use this method), which is called Incremental Spatial Autocorrelation, in the Supplementary Spatial Statistics Toolbox . The output that you're seeing looks alright (without having seen your data). It isn't uncommon to see pvalues that are all 0.00000. It means that at every distance you've tried you're getting statistically significant clustering. The key is to look for peaks in the zscores associated with those statistically significant pvalues which occur at a specific distance. Peaks in the zscore represent distances at which the spatial processes promoting clustering are the most pronounced. If you download the Supplementary Spatial Statistics Toolbox there is a folder called Documentation, which has a document that helps you Learn More about Incremental Spatial Autocorrelation. You can also find tons of other resources about the spatial statistics tools here: http://esriurl.com/spatialstats .
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11142011
02:32 PM

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Hi Jeanee, This is a great question, and one that we get quite a bit. With GWR, there is a local linear equation for each feature in the dataset. The equation is weighted so that nearby features have a larger influence on the prediction of yi than features that are farther away. I do know that our consultant�??s GWR software (Fotheringham, Charlton and Martin) does compute pvalues for each coefficient in every one of the local linear equations. However, because doing so is really not appropriate (and we�??ve discussed this with our consultants and they agree with that assessment), we do not report the coefficient pvalues for our ArcGIS GWR tool. I know our consultants are looking into other methods for computing those pvalues that might be appropriate, but I don�??t believe they have come up with an ideal solution. Because GWR does not have the strong diagnostics (like pvalues, as just one example) that OLS does, we very strongly recommend finding a properly specified OLS model before moving to GWR. Unless you are only interested in predictions (not interested in the coefficients�?� in variable relationships), you cannot trust GWR results unless you can be sure you�??ve found all of the key explanatory variables to model your dependent variable (you can see this easily: run OLS or GWR with 1 important explanatory variable and examine the coefficients; add a second important explanatory variable and notice that the coefficient values change�?� sometimes dramatically; the coefficient values can change 180 degrees, in fact). Having said that, we have just released a tool and documentation on the Geoprocessing Resource Center to help you find a properly specified OLS model: Exploratory Regression and �??What they don�??t tell you about regression analysis�?�. The Exploratory Regression tool is similar to Stepwise Regression except instead of just looking for high Adj R2 values, it looks for models that meet all of the assumptions of the OLS method (no variable redundancy, no spatial autocorrelation in regression residuals, no model bias, statistically significant coefficients�?�). To download this tool and the associated documentation, check out http://esriurl.com/spatialstats (look for Supplementary Spatial Statistics). I took this text right out of this forum post , which also has some additional useful information about using condition numbers and local rsquared results of GWR to see how well you're doing, as well as some other information about moving to GWR from OLS.
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11142011
02:24 PM

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Hi Stephen, Sorry that you've run into this issue! Actually, this sounds like a known issue that is on our list of bugs to fix. Basically, what's happening is that we are doing all of the mathematical calculations using double precision, and that is what's used to create the actual geometry of the output feature. The bug is that we are creating the xcoord field and the ycoord field as "Floats" with only single precision, which is why you're seeing differences when you run the Add XY Coordinates tool. So, the true geometry of the feature is correct, but we are missing precision in the fields where we write the coordinates. If you don't mind, we'd like to see if a simple code change will fix this issue for you. You'll have to find the MeanCenter.py file, which will be located here: C:\Program Files (x86)(**Or wherever you have ArcGIS installed)**\ArcGIS\Desktop10.1\ArcToolbox\Scripts. 1. The first thing to do is rename that file to MeanCenter_Orig.py (this way you'll have the original saved somewhere just in case) 2. Then, open up the MeanCenter_Orig.py, and do a "Save As" and name it MeanCenter.py (the file has to have this name to be found by the Mean Center tool, so you'll want to make sure the file you update has this name) 3. Once you've done this, do a search for the words "Add Field Names". In this section of the code you will see something that looks like this: for fieldName in dataFieldNames: UTILS.addEmptyField(outputFC, fieldName, "FLOAT") 4. What you want to do is change the word "FLOAT" to "DOUBLE". 5. Save your changes. Once you've made the change the xcoord and ycoord fields should be created as doubles, which means that they should have the right precision and you should no longer see any difference from when you run the Add XY Coordinates tool. If you are still seeing differences, please let us know so that we can figure out what's going on! Thanks so much for bringing this to our attention, and again I'm very sorry that you've run into this! Lauren Rosenshein Geoprocessing Product Engineer
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11142011
01:16 PM

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Hi gbateson, I'm really sorry that you're running into this problem too! We'd really like to reproduce the issue so that we can figure out what's going on. Would you be willing to share your data with us so that we can figure this out? I'll also need a breakdown of exactly how you're filling out the tool parameters (a screenshot would work). Again, I'm very sorry that you're having trouble and I hope we can get it figured out soon! Lauren Rosenshein Geoprocessing Product Engineer
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11142011
07:03 AM

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Hi Stephanie, There are tons of resources that will help you get started with your hot spot analysis. You can find links to a lot of our resources here: http://esriurl.com/spatialstats . A good place to start might be several of the short videos, including Performing Proper Density Analysis , Hot Spot Analysis Part 1 , Hot Spot Analysis Part 2 , Hot Spot Analysis Part 3 , and a onehour free seminar called Introduction to Spatial Pattern Analysis . There is also a Hot Spot Analysis Tutorial which I think you'll find very useful. It walks step by step through performing a hot spot analysis, and helps you understand the decisions that you're making along the way.
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11102011
07:01 AM

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Hi Ling Xue, There is actually a tool to do this in the Data Management Toolbox called Table to Ellipse . It should help you do what you want.
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