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Hi Jian, I think I may know why you are getting those results, but let's make sure I understand what you've done first: 1) Your Conceptualization of Spatial Relationships is Inverse Distance 2) You've set Number of Neighbors to 8 to ensure each feature has at least 8 neighbors 3) You are taking the default threshold distance (you didn't enter anything for Threshold Distance) 4) Row Standardization was checked ON I did the above and got expected results with and without Row Standardization. As expected, the weights were different for feature pairs. You, however, are seeing identical weights for all neighbors associated with a particular feature. This is what I think might be happening: Because Inverse Distance is unstable for distances less than 1, our inverse distance calculation treats all distances less than 1 as 1. Suppose you are working in a small-ish study area and are using unprojected data (Geographic Coordinate System instead of a Projected Coordinate System) so that your units are in Degrees. With unprojected data, for a study area that has less than a 1 degree extent, all of your distances will be less than 1.0. All of the weights will get set to 1.0, and when you row standardize all of the weights for a feature's neighbors will be equal. To remedy, please project your data prior to analysis (always a good idea, but especially a good idea when your analyses involve distance measurements). If this is *not* what's happening I will need additional information so that I can try to reproduce the problem. What version of ArcGIS are you using? Might you be able to send me your data? (I would not need any of the attributes, only the feature geometry). Thanks for asking your question! I hope this resolves your problem; if not we'll try again 🙂 Best wishes, Lauren M. Scott, PhD ESRI Geoprocessing, Spatial Statistics Thanks indeed! You are right, it was because I used a GCS and almost all features were in 1 degree of unit which made all spatial weights equal to 1. I've changed to PCS instead and gotten the reasonable result. 🙂 Just another question: while doing an OLS analysis, does a perfect standard normal distribution of OLS model residuals means the model has already include all important factors, so the spatial autocorrelation analysis for residuals is not necessary any more? (I think no matter what's the residuals distribution like, the spatial autocorrelation is still needed... so there is not direct relationship between these two tests... I guess.) And, is there any relationship between Koenker (BP) statistics and spatial autocorrelation for residuals distribution? I feel they somehow give similar implications... Finally, I think there might be a mistake in the Anselin Local Moran's I equation in the "Spatial Statistical Toolbox-Mapping Clusters Toolset" ArcGIS 10 online reference. The second "Xi" should be "Xj", I suppose. see: http://help.arcgis.com/en/arcgisdesktop/10.0/help/index.html#/How_Cluster_and_Outlier_Analysis_Anselin_Local_Moran_s_I_works/005p00000012000000/ Thank you very much again 😮 Jian
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01-09-2011
05:41 AM
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I created a spatial weight matrix table using the "Inverse distance" in Conceptualization of Spatial Relationships. I set the "Nearest Neighbors" as 8. It's weird that in each neighboring region, the weights for every pair of features are exactly same! For example: Feature from i to j and weight: 20 22 0.0769 20 21 0.0769 20 9 0.0769 .... ... .... 20 29 0.0769 the weight sum is 1. But I thought under the "Inverse distance" option, weights should reflect the distances between features. Apparently, the distance of feature 20 to 22 is different with feature 20 to feature 21, but why same weights were given...??? Thanks so much!!
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01-06-2011
02:35 PM
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How to open a .swm table (generated by "Generate Spatial Weights Matrix" in spatial statistics toolset)??? I want to use the table content outside ArcGIS.... thanks! Jian
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12-29-2010
06:11 AM
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For the script as below, can I directly use fieldname, rather than newName in SQL? (so delete newName = arcpy.AddFieldDelimiters("C:/Data", fieldName) ...) If not, why? When to use AddFieldDelimiters? Any difference to ValidateFieldName? Thanks indeed!! import arcpy from arcpy import env fieldName = arcpy.GetParameterAsText(0) wkspace = arcpy.GetParameterAsText(1) in_features = arcpy.GetParameterAsText(2) out_feat_class = arcpy.GetParameterAsText(3) stateVal = arcpy.GetParameterAstext(4) # AddFieldDelimieters will return a field name will the proper # field delimiters for the workspace specified. # newName = arcpy.AddFieldDelimiters("C:/Data", fieldName) # Use delimited field for Select tool SQL expression # sqlExp = newName + " = " + stateVal env.workspace = wkspace arcpy.Select_analysis(in_features, out_feat_class, sqlExp)
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12-07-2010
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it perfectly works, thanks! I think my problem is the SQL sentence .., such as {OIDFieldName + "= " + str(OIDFieldValue)}. I didn't know the expression: + " = " + ... Any suggestions on manuals/references for SQL writing? best Jian
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11-24-2010
12:53 PM
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how to iterate a function as: rows=gp.SearchCursor(featureclass) row=rows.Next() while row: gp.select_analysis(row,output) row=rows.Next() so that I would be able to select a feature record from row1 to row n in a featurecalss seperately. But clearly, "select_analysis" doesn't accept "row" as a leagal input... SO any alternatives? I was thinking of SQL in {where clause}, but how to write the SQL codes (it seems SQL dosen't allow an iterating variable either, like {where i=range(1,100), "OBJECTID=i"} ?) thanks indeed!!
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11-24-2010
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