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Thanks for your response. so when I am doing the analysis in U.S. (which provides predictive traffic), does it ignore historical and live traffic all together?
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11-16-2023
10:42 AM
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I am conducting network analysis using ArcGIS Pro. I am not setting a specific date or time for the analysis and I am measuring drive time from point A to B. The below page says that "the analysis will be solved in a time neutral way if the analysis is not explicitly configured to use a date and time." Question: what does a time-neutral way mean? does it average travel time over all days of a week and a few time points? does it randomly average travel time? Thanks for your help on this. https://pro.arcgis.com/en/pro-app/latest/help/analysis/networks/dates-and-times.htm
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11-16-2023
09:58 AM
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I know that this question has been asked in other ways but I am not still able to find an answer for it. I want to calculate the population-weighted centroids of census tracts within the Contiguous US using the census block populations. I am using the Mean Center and I have defined the weights as census block populations, and for the Case field, I used the census tracts FIPS Code. There are 83,776 tracts in the Contiguous US but the outcome has only 28,798 records. And most of the points are not projected on the right tract (for instance, the centroid of a tract in NY is shown in FL). I have also used the "USA_Contiguous_Equidistant_Conic" projection system for all my data and also my main map. The Datum is also NAD83. I know that Census provides Population Mean Center but I want to find a way to get those results by myself. Please assist me if you can. Thank you
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06-29-2022
01:36 PM
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Have you been able to find any simpler approach? I am using claims data and have the same problem. I wonder whether overlapping points might be a problem for GWR.
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12-09-2021
02:24 PM
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Hi, I am trying to apply GWR on patients' claims data. for every record of patients, I have demographic info and their ZIP Codes. so if I plot them, they will be mapped on each other at the centroid of ZIP Codes. 1. GWR works on my data but I wonder whether the results are reliable for points data like this? 2. I have a binary outcome and several binary independent variables. While I can choose Binary for the outcome variable in the GWR settings, can I use binary independent variables (or even categorical variables with more than 2 classes) in GWR? if yes, I wonder how I should interpret the results for independent variables' coefficients? let's say I code males as 0 and females as 1. so the coefficients should be interpreted for females as they are coded 1? what if they are coded as males with 1 and females with 2? Thanks for the feedback in advance.
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11-24-2021
01:17 PM
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Thanks for the question and answer. What if I was predicting a binary outcome variable? can I use binary exploratory variables in that case? also after running the GWR, how should I interpret the results? let's say I code males as 0 and females as 1. so the coefficients should be interpreted for females as they are coded 1?
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11-24-2021
01:04 PM
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I want to develop a multivariate logistic regression to model the odds of opioid overdose deaths at the ZIP Code level. Since the logistic regression does not handle spatial autocorrelation, I need to check whether my dependent/outcome variable is spatially autocorrelated or not (measuring the Moran’s I on the occurrences of opioid overdose death). I wonder if the outcome was spatially autocorrelated, how I can address that in ArcGIS Pro? I know that people use the Bayesian hierarchical spatial model to account for spatial autocorrelation but how can I use such a method in ArcGIS? Does the GWR method account for spatial autocorrelation?
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10-27-2021
10:49 AM
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yes, it is. I have projected the shapefile to NAD83 as well.
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05-24-2021
11:22 AM
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I am trying to confine the geoprocessing analyses to the boundary of the State of Utah. I have set the Processing Extent in the Environment window from the Analyses ribbon tab to be the same as Utah Shapefile. However, the output of my analyses goes beyond the boundary of the Utah shapefile (please see attached). I know that Business Analysis might solve this issue but I do not have the license for that. Would you please recommend another approach?
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05-24-2021
11:04 AM
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Thank you, Tim. That is interesting to know about the Mean Center tool.
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05-24-2021
08:39 AM
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I am trying to calculate the population-weighted centroids of Utah's census tracts using the census blocks population in ArcGIS Pro. I have joined the census blocks population of 2010 to the census block shapefile of 2010 and have projected the shapefile to NAD83 (for Utah Central FIPS 4302 US Feet). After using the Mean Center tool and assigning the census block population to Weight Field and tract codes to Case Field, I get the results. However, some of the centers are not within the tract's boundaries. For instance, the population-weighted centroid of Tract 110701 is plotted on the 974300 census tract. Any idea what the problem is and how to fix it? I appreciate your feedback.
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05-21-2021
10:11 AM
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Thank you all. I finally understood what you were pointing at. I was trying to project the map, not the layer. Now, I projected the layer using a PCS appropriate for Utah and things work.
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10-10-2018
12:01 PM
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I have the ArcGIS Pro 2.2.1 with all the features installed. I am trying to create space-time cube using the tool, however, when I try to run it, I get this error: Error 001022: This tool requires a projected coordinate system. I have defined both "Current XY" and "Current Z" coordinate of the map (Utah; as can be seen attached) to GCS North American 1983 and NAD 1983 respectively, so I have no idea why I get this error again and again. Do you have any idea? Moreover, I have also used the "Project" tool to project the Layer (Utah_Zipcode_Time) that I want to use in the "Create Space Time Cube" tool. This is a shapefile with a time-based variable, count of incidence, and many other variables in it.
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10-09-2018
01:08 PM
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Title | Kudos | Posted |
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2 | 06-29-2022 01:36 PM | |
1 | 05-24-2021 11:38 AM | |
1 | 10-10-2018 12:01 PM |
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