Subject: Marine Geospatial Ecology Tools (MGET) help
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| From: | "Jason Roberts" <> |
|---|---|
| To: | "'Nadine Golden'" <> |
| Cc: | <> |
| Subject: | RE: [mget-help] Fit GLM Coefficients |
| Date: | Tue, 22 Feb 2011 17:51:38 -0500 |
Hi Nadine, As far as I could tell from looking at the history of our revision control system, we have not made any changes to Fit GLM or Predict GLM since MGET 0.8a8. The code for those should be identical between 0.8a8 and 0.8a21. Does your geoprocessing model start with Fit GLM or does it start with something earlier? For example, did you sample some rasters prior to calling Fit GLM, or something like that? I wonder if the input data are exactly the same as before. If you have a copy of the old data you used when calling Fit GLM, you could compare it to the new data using ArcGIS’s Data Comparison tools (under Data Management toolset) and see if anything has changed. Other than that, I’m not sure what to suggest, given that it looks like the versions of all other programs are the same. To test whether the MGET version is affecting things, you could uninstall 0.8a21 and try 0.8a8 again, downloadable from the following link: Best, Jason From: Nadine Golden [mailto:] Hi I am a GIS Technician at the USGS Coastal and Marine Geology. We used MGET "Fit GLM" and "Predict GLM" successfully this summer to combine ground truth observations, depth, class, and defined blocks to predict the distribution of benthic organisms. By successful, I mean that the coefficients in the "Fit GLM" exactly matched the coefficients we received when running the "R Formula" in "R Statistical package" independent of MGET. Recently we reran our five taxa models and are getting "Fit GLM" coefficients that are not the same as the coefficient we got last time. This issue is occurring in both the exact same ArcGIS project (ArcGIS 9.3.1, Python 2.5, MGET .8a8, and R 2.6.2) where it successfully ran this summer and in a new MGET .8a21 ( I was unable to locate MGET .8a8. All other programs are the same: ArcGIS 9.3.1, Python 2.5, and R2.6.2). As you can imagine, the predictions look different ranging from extremely different o slightly different? Do you have any recommendations on what to try or why this could be happening? Thank you for any advice, Best regards Nadine Nadine Golden U.S. Geological Survey Pacific Coastal and Marine Science Center Santa Cruz, CA (831) 427-4730 |